SEARCH SESSIONS
SEARCH SESSIONS

Search All
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC ON-DEMAND

Topic(s) Filter: Intelligent Video Analytics
Presentation
Media
Abstract:
Well present an end-to-end workflow for damage detection and disaster response using Esris ArcGIS AI capabilities and NVIDIA GPUs. Identifying damaged buildings and roads following disasters is a key prerequisite in allocating potentially life-saving ...Read More
Abstract:
Well present an end-to-end workflow for damage detection and disaster response using Esris ArcGIS AI capabilities and NVIDIA GPUs. Identifying damaged buildings and roads following disasters is a key prerequisite in allocating potentially life-saving resources. Manual identification takes significant manpower and time, which are both critical. With the increased accessibility of drone and satellite imagery, along with computer vision models, weve made the complete automation of damaged structure detection possible. Our workflow includes imagery access and management; model training and deployment to production; massive inference at scale; and the creation of meaningful geospatial information products.  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91516
Download:
Share:
 
Abstract:
Well discuss how cameras using the latest AI algorithms can understand the physical world and help digitize and optimize business processes. To work in real-time while staying cost-effective and protecting privacy, these advanced video analytics appl ...Read More
Abstract:
Well discuss how cameras using the latest AI algorithms can understand the physical world and help digitize and optimize business processes. To work in real-time while staying cost-effective and protecting privacy, these advanced video analytics applications must analyze data at the edge. Well demonstrate how to build, deploy, and operate these applications using NVIDIA DeepStream and Azure IoT Edge on devices ranging from a Jetson Nano to a T4 server.  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91421
Download:
Share:
 
Abstract:
Computer vision today still relies on conventional camera capture that was invented decades ago to accommodate the human visual system.  Yet computers and humans see the world very differently.  What works for human vision does not cor ...Read More
Abstract:

Computer vision today still relies on conventional camera capture that was invented decades ago to accommodate the human visual system.  Yet computers and humans see the world very differently.  What works for human vision does not correlate for computer vision, and vice versa.  This is especially true for computer vision based on deep convolutional networks. We need better vision for computer vision.  Using GPUs and deep learning, we're able to reverse the resolution degrading effects of conventional visual capture, then reconstruct on demand to radically improve the accuracy and processing efficiency of computer vision applications.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S91054
Streaming:
Download:
Share:
 
Abstract:
We'll discuss our Argus intelligent video analysis product for the logistics industry, powered by NVIDIA Tesla P4, which was deployed at more than 100 sorting centers and distribution center over the past year. Learn about our algorithms, which tack ...Read More
Abstract:
We'll discuss our Argus intelligent video analysis product for the logistics industry, powered by NVIDIA Tesla P4, which was deployed at more than 100 sorting centers and distribution center over the past year. Learn about our algorithms, which tackle loading-gate working status and staff-efficiency analysis, vehicle license plate recognition, vehicle loading rate detection, active new data sample collection, fine-grained illegal throwing behavior detection, and ranking. We'll provide details of our flexible computing pipeline implementation and its integration based on the NVIDIA Metropolis software stack. We'll also cover in-production performance metrics with Tesla P4/Jetson Xavier devices and discuss deployment considerations.  Back
 
Topics:
Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9154
Streaming:
Download:
Share:
 
Abstract:
We'll discuss how we're using several Jetson TX2-based edge computing devices and LPWAN networks to monitor in real time the flow of vehicles and pedestrians in a network. In particular, we'll describe our work to better understand and predict ped ...Read More
Abstract:
We'll discuss how we're using several Jetson TX2-based edge computing devices and LPWAN networks to monitor in real time the flow of vehicles and pedestrians in a network. In particular, we'll describe our work to better understand and predict pedestrian and vehicle flow around the Liverpool CBD to ease congestion, provide better transport options, and improve health and safety. In our solution, each device in the monitored network processes the live feed from its own camera. We'll explain how we use the YOLO v3 object detector to analyze these frames and extract the pedestrians and vehicles in each, then pass this information onto a tracker algorithm (Kalman filter) to determine their trajectories. After a frame is processed, it is discarded and only aggregated indicators are sent over the LPWAN network to a dashboard to reduce privacy concerns and bandwidth requirements.  Back
 
Topics:
Intelligent Video Analytics, Intelligent Machines, IoT & Robotics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9206
Streaming:
Download:
Share:
 
Abstract:
We will discuss 3D vehicle and pedestrian tracking and localization by monocular surveillance cameras for an AI city. We'll explain how to use 2D detections to localize vehicles in 3D world coordinates and how to estimate the GPS speed with a tracki ...Read More
Abstract:
We will discuss 3D vehicle and pedestrian tracking and localization by monocular surveillance cameras for an AI city. We'll explain how to use 2D detections to localize vehicles in 3D world coordinates and how to estimate the GPS speed with a tracking approach. We will also examine how appearance features and temporal consistency combine to define clustering loss between two tracklets and how we used five clustering operations for loss minimization.  Back
 
Topics:
Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9266
Streaming:
Download:
Share:
 
Abstract:
Learn how to get started deploying AI-based video analytic solutions using the NVIDIA DeepStream SDK. We'll walk through steps required to set up an environment on Jetson and Tesla and discuss best practices for selecting cameras and guiding design ...Read More
Abstract:
Learn how to get started deploying AI-based video analytic solutions using the NVIDIA DeepStream SDK. We'll walk through steps required to set up an environment on Jetson and Tesla and discuss best practices for selecting cameras and guiding design for data center and edge computing. We'll also provide an example that uses samples in the SDK to create a concurrent neural network in a multi-camera tracking environment.  Back
 
Topics:
Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9545
Streaming:
Download:
Share:
 
Abstract:
Applications such as climate science, intelligent transportation, aerospace control, and sports analytics apply machine learning for large-scale spatiotemporal data. This data is often nonlinear, high-dimensional, and demonstrates complex spatial and ...Read More
Abstract:
Applications such as climate science, intelligent transportation, aerospace control, and sports analytics apply machine learning for large-scale spatiotemporal data. This data is often nonlinear, high-dimensional, and demonstrates complex spatial and temporal correlation. Existing deep learning models cannot handle complex spatiotemporal dependency structures. We'll explain how to design deep learning models to learn from large-scale spatiotemporal data, especially for dealing with non-Euclidean geometry, long-term dependencies, and logical and physical constraints. We'll showcase the application of these models to problems such as long-term forecasting for transportation, long-range trajectories synthesis for sports analytics, and combating ground effect in quadcopter landing for aerospace control.l).  Back
 
Topics:
Intelligent Video Analytics, Intelligent Machines, IoT & Robotics, AI & Deep Learning Research
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9806
Streaming:
Download:
Share:
 
Abstract:
We'll discuss how Baidu leverages NVIDIA's AI power for video content analysis, video content regulation and intelligent video editing, and explain how to fulfill external custom model requirements. We'll also outline how we use NVIDIA's Tensor C ...Read More
Abstract:
We'll discuss how Baidu leverages NVIDIA's AI power for video content analysis, video content regulation and intelligent video editing, and explain how to fulfill external custom model requirements. We'll also outline how we use NVIDIA's Tensor Core and Apex toolkit to boost the training speed, ensure the model on-time delivery, and describe how we use the TensorRT high-performance inference engine to provide the online service, model pruning/quatilization, and Jetson mobile platform.  Back
 
Topics:
Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9862
Streaming:
Download:
Share:
 
Abstract:
We'll present a novel real-time framework based on NVIDIA Volta architecture for real-time automatic incident detection, which plays an important role in transportation systems. This framework is mandatory in every tunnel in Europe and is being depl ...Read More
Abstract:
We'll present a novel real-time framework based on NVIDIA Volta architecture for real-time automatic incident detection, which plays an important role in transportation systems. This framework is mandatory in every tunnel in Europe and is being deployed to the more than 80 tunnels we manage in France and elsewhere in Europe. We'll describe our real-time automatic incident detection solution and discuss how it outperforms traditional systems based on classical image processing techniques, which are inefficient and produce many false positives. We'll also detail the challenges we faced, including the need to minimize hardware cost, provide highly precise detection, and keep computation time very low. The complexity of this problem increases with the number of the cameras, which range from 50-380 per tunnel.  Back
 
Topics:
Intelligent Video Analytics, Autonomous Vehicles, AI Application, Deployment & Inference
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9868
Streaming:
Share:
 
Abstract:
The meta-data provided by content creators is not sufficient to create the exciting and customer-focused discovery and navigational experiences that premium video customers demand from their services these days. In our talk we will describe how Comca ...Read More
Abstract:
The meta-data provided by content creators is not sufficient to create the exciting and customer-focused discovery and navigational experiences that premium video customers demand from their services these days. In our talk we will describe how Comcast uses machine learning and AI such as computer vision and natural language processing technologies to better understand the content distributed on our platform. We will conclude with examples of how this extracted information can then be used to create novel and compelling offerings which lead to a better customer experience and higher engagement with our products.  Back
 
Topics:
Intelligent Video Analytics, Intelligent Machines, IoT & Robotics, AI & Deep Learning Research
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9875
Streaming:
Share:
 
Abstract:
We address the recognition of agent-in-place actions, which are associated with agents who perform them and places where they occur, in the context of outdoor home monitoring. We introduce a representation of the geometry and topology of scene layout ...Read More
Abstract:
We address the recognition of agent-in-place actions, which are associated with agents who perform them and places where they occur, in the context of outdoor home monitoring. We introduce a representation of the geometry and topology of scene layouts so that a network can generalize from the layouts observed in the training set to unseen layouts in the test set. We introduce the Agent-in-Place Action dataset to show that our method allows neural network models to generalize significantly better to unseen scenes.   Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2018
Session ID:
DC8128
Streaming:
Share:
 
Abstract:
This talk explores how DeepStream enables developers to create high-stream density applications with deep learning and accelerated multimedia image processing, building IVA solutions at scale. Leverage a heterogeneous concurrent neural network a ...Read More
Abstract:

This talk explores how DeepStream enables developers to create high-stream density applications with deep learning and accelerated multimedia image processing, building IVA solutions at scale. Leverage a heterogeneous concurrent neural network architecture to bring in different deep learning techniques for more intelligent insights. The framework makes it easy to create flexible and intuitive graph-based applications, resulting in highly optimized pipelines for maximum throughput.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2018
Session ID:
DC8156
Streaming:
Download:
Share:
 
Abstract:
Learn how we overcame the odds of certifying computer vision and AI systems in an industry as risk adverse as the air traffic control sector. We use off-the-shelf cameras deployed in an airport environment to provide an out the window view of th ...Read More
Abstract:

Learn how we overcame the odds of certifying computer vision and AI systems in an industry as risk adverse as the air traffic control sector. We use off-the-shelf cameras deployed in an airport environment to provide an out the window view of the airfield, create an enriched augmented reality view for better situational awareness, contingency and redundancy. In this talk, we take you through the steps from developing an AI using Nvidia frameworks, to deploying a camera system at an airport for air traffic control use as an imaging system as well as a tracking system using AI technology such as artificial neural networks. All the way through user acceptance tests and certification. This talk is intended as a lessons learned for your next project in smart cities or aerospace. The main focus of this talk lays on the tools used to develop AI and the tools used to understand and visualize neural networks.

  Back
 
Topics:
Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Washington D.C.
Year:
2018
Session ID:
DC8161
Streaming:
Download:
Share:
 
Abstract:
Cities are always looking for new ways to maintain high standards of living, better connect with citizens and find ways to save moneyââ¬âall while serving growing populations. As city population densities increase an ...Read More
Abstract:

Cities are always looking for new ways to maintain high standards of living, better connect with citizens and find ways to save moneyââ¬âall while serving growing populations. As city population densities increase and cities strive to increase walkability and mobility for their citizens, they have a big focus on a holistic approach to traffic safety. As part of their efforts to become smarter, more and more cities are turning to the Internet of Things (IoT) and Machine-to-Machine (M2M) technologies to improve municipal services, create additional sources of revenue, and enable city management in new and creative ways.

  Back
 
Topics:
Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Washington D.C.
Year:
2018
Session ID:
DC8173
Streaming:
Share:
 
Abstract:
From managing wilderness to urban environments, deploying & integrating visual intelligence is critical but challenging. We will discuss a number of scenarios where deploying deep learning right at the edge solves scalability, networking, and res ...Read More
Abstract:
From managing wilderness to urban environments, deploying & integrating visual intelligence is critical but challenging. We will discuss a number of scenarios where deploying deep learning right at the edge solves scalability, networking, and responsiveness constraints. Boulder AI will showcase how deep learning and NVIDIA Jetson accelerated computing enabled cameras has solved key problems in hydroelectric dams , agriculture, and urban traffic systems. This talk will also cover the benefits and challenges of leveraging and analyzing 12 bit high fidelity imagery in diverse and challenging outdoor environments.  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2018
Session ID:
DC8213
Streaming:
Share:
 
Abstract:
Learn how GPU computing and deep learning can be utilized for the detection of cracks, potholes and patches on road pavement surface. In recent years, the increasing number of vehicles on the road is driving the demand for automated pavement distress ...Read More
Abstract:
Learn how GPU computing and deep learning can be utilized for the detection of cracks, potholes and patches on road pavement surface. In recent years, the increasing number of vehicles on the road is driving the demand for automated pavement distress detection. To respond to this demand, we present a decentralized system for distress detection based on common passenger vehicles. By performing image pre-processing steps and calculating textural features and wavelet transform on GPUs, real-time pavement distress detection is enabled. Deep learning is employed to determine the type of the distress. The approach was tested on 38,000 images and an accuracy of 93% was achieved. To improve the reliability of the pavement distress detection methodology, an ensemble method for distress detection was developed by aggregating results obtained by different vehicles.  Back
 
Topics:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8174
Streaming:
Download:
Share:
 
Abstract:
Learn how to develop an Artificial Intelligence system to localize and recognize food on trays to generate a purchase ticket in a check out process.
(1) Solving a real business problem using Deep Learning advanced technology based on obje ...Read More
Abstract:

Learn how to develop an Artificial Intelligence system to localize and recognize food on trays to generate a purchase ticket in a check out process.
(1) Solving a real business problem using Deep Learning advanced technology based on object detection and localization.
(2) Combining a pipeline of models to improve accuracy, precision and with reasonable recall levels.
(3) Discovering how to develop and train a model in the cloud to be used embedded in an NVIDIA Jetson TX1 device.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8236
Streaming:
Download:
Share:
 
Abstract:
Identifying and analyzing objects on images or video is a well-established area of visual computing using artificial intelligence. But what happens, when there is no light ?. Raypack.ai shows, how you could use ai to analyze images and video streams ...Read More
Abstract:
Identifying and analyzing objects on images or video is a well-established area of visual computing using artificial intelligence. But what happens, when there is no light ?. Raypack.ai shows, how you could use ai to analyze images and video streams originated from thermal cameras and other kinds of sensors. Besides detecting objects, this technology is offering a variety of totally new, outstanding use cases.  Back
 
Topics:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8240
Streaming:
Download:
Share:
 
Abstract:
Detecting road users in real-time is key to enabling safe autonomous driving applications in crowded urban environments. The talk presents a distributed sensor infrastructure being deployed in the city of Modena (Italy) at the heart of the Itali ...Read More
Abstract:

Detecting road users in real-time is key to enabling safe autonomous driving applications in crowded urban environments. The talk presents a distributed sensor infrastructure being deployed in the city of Modena (Italy) at the heart of the Italian 'Motor Valley'. Modena's Automotive Smart Area (MASA) connects hundreds of smart cameras, supporting embedded GPU modules for edge-side real-time detection, with higher performance GPU (fog) nodes at block level and low latency wireless V2X communication. A distributed deep learning paradigm balances precision and response time to give autonomous vehicles the required sensing support in a densely populated urban environment. The infrastructure will exploit a novel software architecture to help programmers and big data practitioners combine data-in-motion and data-at-rest analysis while providing Real-Time guarantees. MASA; funded under the European project CLASS, is an open testbench where interested partners may deploy and test next-generation AD applications in a tightly connected setting.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8254
Streaming:
Download:
Share:
 
Abstract:
Modern computing hardware and NVIDIA Jetson TX1 / TX2 performance create new possibilities for smart city applications and retail, parking lot, and drone industries. We'll present on how the PIXEVIA system covers vision processing and AI tas ...Read More
Abstract:

Modern computing hardware and NVIDIA Jetson TX1 / TX2 performance create new possibilities for smart city applications and retail, parking lot, and drone industries. We'll present on how the PIXEVIA system covers vision processing and AI tasks using deep neural networks; learning using computer generated images for number plate recognition; and self-supervised learning for vehicle detection. We will explore methods for orchestrating and combining information from different type of neural networks (from SSDs, Mask-RCNNs to attention based RNNs). Real-world use cases for parking lots (empty parking space detection, number plate recognition) and retail industries (amount of stock on the shelf calculation, people counting with age and gender recognition) will also be presented.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8341
Streaming:
Download:
Share:
 
Abstract:
Learn how Edge Computing can help you find the parking spot right next to you! We will present a scalable end-to-end architecture that, leveraging on Nvidia Jetson computational power to detect free parking spaces, is able to drive the user minimizin ...Read More
Abstract:
Learn how Edge Computing can help you find the parking spot right next to you! We will present a scalable end-to-end architecture that, leveraging on Nvidia Jetson computational power to detect free parking spaces, is able to drive the user minimizing the time spent looking for parking. Using our pre-trained models, we are able to perform the detection at the edge of the cloud, reducing the bandwidth utilization up to 95% with respect to a streaming-based solution. Using Computer Vision and Machine Learning algorithms, the configuration needed to setup the system takes only a few minutes with minimal user interaction. Our optimized with dual boot operating system and support to failover, moreover, guarantees security against malicious intrusions and reliability in the upgrade procedures.  Back
 
Topics:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8352
Streaming:
Download:
Share:
 
Abstract:
Experience how to make spaces aware of the situation of people and objects. Explore new techniques to build real-time systems that can understand scenes with the help of hemispherical point clouds and AI at the edge. The goal of this session is ...Read More
Abstract:

Experience how to make spaces aware of the situation of people and objects. Explore new techniques to build real-time systems that can understand scenes with the help of hemispherical point clouds and AI at the edge. The goal of this session is to learn new ways of developing scene understanding needed for action and interaction in public spaces or smart homes. The capture, recognition and understanding of all external and internal degrees of freedom of persons and objects and of their respective states give the full information of the observed space.
While hemispherical vision provides advantages for wide-area coverage from a single point of observation, it also introduces new challenges due to its distinct projection geometry. At the example of 3-dimensional people detection and posture recognition, we explain different approaches to use deep neural networks to extract information from hemispherical RGB-D data. The talk focuses on providing an overview over methods, which attendees can be apply to custom projects and run on Jetson in real-time.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8355
Streaming:
Download:
Share:
 
Abstract:
With billions of real-time datapoints and cutting-edge neural networks, Vivacity Labs is providing deep insights into the behaviour of transport networks and transforming urban mobility infrastructure. Over 2500 GPU accelerated camera sensors have be ...Read More
Abstract:
With billions of real-time datapoints and cutting-edge neural networks, Vivacity Labs is providing deep insights into the behaviour of transport networks and transforming urban mobility infrastructure. Over 2500 GPU accelerated camera sensors have been installed city-wide in Milton Keynes UK, able to count and classify vehicle movements in real-time using deep learning. Live predictive models were built based on a proprietary combination of long short-term memory neural networks and evolutionary algorithms. Descriptive modelling has also been used to identify anomalies, correlations, and patterns in the data. Vivacity Labs is now delivering proof of concept systems which continuously and automatically learn and adapt to optimise traffic networks.  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8427
Streaming:
Download:
Share:
 
Abstract:
SmartCow will demonstrate deep learning pipeline (Annotation, visualization, training) for large data-sets, various internal tools including SmartCow dynamic HPC container deployment software and inference software on on DGX, annotation framework, vi ...Read More
Abstract:
SmartCow will demonstrate deep learning pipeline (Annotation, visualization, training) for large data-sets, various internal tools including SmartCow dynamic HPC container deployment software and inference software on on DGX, annotation framework, visualisation framework, deployment of deep learning models remotely on edge cameras (Jetson TX2 cameras). Take away: Learn how to setup pipeline for annotation of data sets. Understanding how to setup proper deployment for edge cameras.   Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8525
Streaming:
Download:
Share:
 
Abstract:
Learn how Verizon is helping create safer streets, reducing traffic congestion, aiding the navigation of both vehicles and pedestrians, and reducing energy costs and consumption through AI-enabled sensor based networks that leverage LED street l ...Read More
Abstract:

Learn how Verizon is helping create safer streets, reducing traffic congestion, aiding the navigation of both vehicles and pedestrians, and reducing energy costs and consumption through AI-enabled sensor based networks that leverage LED street lighting infrastructure. We will discuss our Vision Zero application and how use deep learning to recognize, detect, classify and concurrently track vehicles in traffic, pedestrians, bicyclists, and parked cars, and turn it into actionable data to help make better urban planning decisions and quantify the results.

  Back
 
Topics:
Intelligent Video Analytics, Intelligent Machines, IoT & Robotics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8966
Streaming:
Share:
 
Abstract:
Introduction to high performance deep learning inference for video analytics. NVIDIA DeepStreamSDK simplifies the development of scalable intelligent video analytics (IVA) applications powered by deep learning for smart cities and hyperscale datacent ...Read More
Abstract:
Introduction to high performance deep learning inference for video analytics. NVIDIA DeepStreamSDK simplifies the development of scalable intelligent video analytics (IVA) applications powered by deep learning for smart cities and hyperscale datacenters.   Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S81047
Streaming:
Download:
Share:
 
Abstract:
This session will introduce how Huawei applies heterogeneous computing to smart cities, and will also introduce some successful practices and cases. With the advance of smart city solutions, immense compute power is required for processing various ap ...Read More
Abstract:
This session will introduce how Huawei applies heterogeneous computing to smart cities, and will also introduce some successful practices and cases. With the advance of smart city solutions, immense compute power is required for processing various applications to meet purposes such as pedestrian and vehicle monitoring, traffic optimization, and suspect identification. General-purpose x86 computing has fallen short of such demands, and heterogeneous computing provides an ideal answer to these requirements.  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S81000
Streaming:
Download:
Share:
 
Abstract:
Learn how to simulate transportation systems and crowds for smart city applications at massive scale. This talk will give insights into novel algorithms and techniques which are being applied to: 1) National (entire UK) scale road network flow s ...Read More
Abstract:

Learn how to simulate transportation systems and crowds for smart city applications at massive scale. This talk will give insights into novel algorithms and techniques which are being applied to: 1) National (entire UK) scale road network flow simulations, 2) City sized simulations of intelligent individually modelled vehicles, and 3) Integrated simulations of national infrastructure with Pedestrian crowds, vehicles and rail. Examples of techniques include low-density high-diameter graph traversal, multi agent simulation and virtual reality interaction using the OmniDeck treadmill and the Oculus Rift.

  Back
 
Topics:
Intelligent Video Analytics, Autonomous Vehicles
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8223
Streaming:
Download:
Share:
 
Abstract:
A variety of aspects of modern video understanding platform will be discussed. We will cover such topics as single stage CNN-based hierarchical object detection for low level image semantics extraction, LSTM neural network architectures for effi ...Read More
Abstract:

A variety of aspects of modern video understanding platform will be discussed. We will cover such topics as single stage CNN-based hierarchical object detection for low level image semantics extraction, LSTM neural network architectures for efficient tracking and behavioral analysis, object descriptors for cross stream similarity. Later on we will talk on the time-optimized video analysis system architecture, which enable processing of multiple streams on a single NVIDIA GPU and running in near-real time. Finally we will demonstrate the system performance on a variety of complex use-cases.

  Back
 
Topics:
Intelligent Video Analytics, AI Startup
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8875
Download:
Share:
 
Abstract:
Parsing millions of video cameras in real time to provide situational awareness is an enormous challenge. We will discuss how YITU Tech has overcome this using GPUs and TensorRT. We learned from 1 billion faces to win first place in face identif ...Read More
Abstract:

Parsing millions of video cameras in real time to provide situational awareness is an enormous challenge. We will discuss how YITU Tech has overcome this using GPUs and TensorRT. We learned from 1 billion faces to win first place in face identification accuracy in FRPC 2017 hosted by NIST. We will show how we analyze data from 10 million cameras using several thousand NVIDIA Tesla P4s and achieve accuracy of 99% in identifying pedestrians with 100 days of data from the cameras.  The result is an ability to do big data analysis on things like population density and traffic flows, that enable the development of smart cities.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8945
Streaming:
Download:
Share:
 
Abstract:
In this talk will discuss how deploying cameras, sensors, and deep learning in commercial vehicles accelerated by NVIDIA Jetson can help analyze the driving environment in real time, improve driver safety, while at the same time performing dynamic HD ...Read More
Abstract:
In this talk will discuss how deploying cameras, sensors, and deep learning in commercial vehicles accelerated by NVIDIA Jetson can help analyze the driving environment in real time, improve driver safety, while at the same time performing dynamic HD mapping.  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8856
Streaming:
Download:
Share:
 
Abstract:
In contrast to traditional CNN training with large offline static datasets, some autonomous machine applications will benefit from training in real-time for mid-mission adjustment and correction. This training will occur on live video streams, with a ...Read More
Abstract:
In contrast to traditional CNN training with large offline static datasets, some autonomous machine applications will benefit from training in real-time for mid-mission adjustment and correction. This training will occur on live video streams, with a human-in-the-loop. We demonstrate and evaluate a system tailored to performing time-ordered online training (ToOT) in the field, capable of training an object detector on a live video stream with minimal input from a human operator. Online training is conducted entirely on an NVIDIA Jetson TX2 onboard an autonomous machine. We first define training benefit as a metric to measure the effectiveness of a user interaction in a ToOT sequence. We then show that we can obtain annotations for training an object detector from single-point clicks. Furthermore, by exploiting the time-ordered nature of the video stream through object tracking, we can increase the average training benefit of human interactions by several times.  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8852
Streaming:
Download:
Share:
 
Abstract:
Basic image processing functions for convolution, morphological, and arithmetic operators are at the heart of many important high-level computer vision algorithms. We'll describe how to implement these routines efficiently on the GPU, using unique G ...Read More
Abstract:
Basic image processing functions for convolution, morphological, and arithmetic operators are at the heart of many important high-level computer vision algorithms. We'll describe how to implement these routines efficiently on the GPU, using unique GPU capabilities like the texture cache and a large register file. We'll give information about several applications where these routines are employed, like film and video restoration (either locally or in the cloud) or automatic real-time quality assessment and automatic camera path calculation (virtual director) in omnidirectional video.  Back
 
Topics:
Intelligent Video Analytics, Virtual Reality & Augmented Reality, Video & Image Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8111
Streaming:
Download:
Share:
 
Abstract:
We will describe a fast and accurate AI-based GPU accelerated Vehicle inspection system which scans the underside of moving vehicles to identify threatening objects or unlawful substances (bombs, unexposed weapons and drugs), vehicle leaks, wear ...Read More
Abstract:

We will describe a fast and accurate AI-based GPU accelerated Vehicle inspection system which scans the underside of moving vehicles to identify threatening objects or unlawful substances (bombs, unexposed weapons and drugs), vehicle leaks, wear and tear, and any damages that would previously go unnoticed.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Israel
Year:
2017
Session ID:
SIL7133
Download:
Share:
 
Abstract:
How can we enable automated AI/ Deep learning based machines to evolve their specialties through colonies of "social networks of intelligent machines" (SNIM)? We will give an example of Qylur's QyNetTM machines cloud concept and ho ...Read More
Abstract:

How can we enable automated AI/ Deep learning based machines to evolve their specialties through colonies of "social networks of intelligent machines" (SNIM)? We will give an example of Qylur's QyNetTM machines cloud concept and how we utilize the power of SNIMs, GPU enabled deep learning and execution at edge systems, to enable a revolution in our guest entry operations and physical security for public venues. From mega events to parks and museums. We will also dream a bit further to how other industrial intelligent machines can benefit from the QyNet SNIM, and also touch on our responsibilities as humans as we enable this disruptive and beneficial revolution to take place.

  Back
 
Topics:
Intelligent Video Analytics, Intelligent Machines, IoT & Robotics
Type:
Talk
Event:
GTC Israel
Year:
2017
Session ID:
SIL7118
Download:
Share:
 
Abstract:
Video is increasingly becoming a key sensor for maintaining security, business performance and efficient operations. This session will discuss the technology and application of BriefCam's video analytics solutions. Topics will include how GP ...Read More
Abstract:

Video is increasingly becoming a key sensor for maintaining security, business performance and efficient operations. This session will discuss the technology and application of BriefCam's video analytics solutions. Topics will include how GPUs and deep learning generates rich metadata from video and how it solves a diverse range of problems and applications.

  Back
 
Topics:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Israel
Year:
2017
Session ID:
SIL7117
Download:
Share:
 
Abstract:
Smart and safe cities need AI. There are approximately 500 million cameras deployed globally today. When it comes to analyzing that data, traditional methods of video analytics often fall short. AI and deep learning can provide the level of accu ...Read More
Abstract:

Smart and safe cities need AI. There are approximately 500 million cameras deployed globally today. When it comes to analyzing that data, traditional methods of video analytics often fall short. AI and deep learning can provide the level of accuracy needed to extract meaningful real-time insights. The result is improved public safety and more efficient city operations. NVIDIA Metropolis is the companys edge-to-cloud platform for the AI City. It includes solutions for deep learning at the edge, in on-prem servers and in the cloud, as well as a comprehensive SDK. During this talk, well provide an overview on NVIDIA Metropolis, its different applications, and its critical role in the creation and expansion of smart and safe cities.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Israel
Year:
2017
Session ID:
SIL7132
Download:
Share:
 
Abstract:
Leveraging NatSec technology to make real-time video streaming from vehicles possible, zero-latency, secure and affordable; and applying the latest generation of FaceRec analytics to ensure only authorised people are behind the wheel. ...Read More
Abstract:

Leveraging NatSec technology to make real-time video streaming from vehicles possible, zero-latency, secure and affordable; and applying the latest generation of FaceRec analytics to ensure only authorised people are behind the wheel.

  Back
 
Topics:
Intelligent Video Analytics, Autonomous Vehicles, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23155
Download:
Share:
 
Abstract:
SeeQuestor uses Deep Learning and Affordable Supercomputers to provide Radically Faster Video Intelligence to Police and Law Enforcement Agencies who need to search 100s or 1,000s of hours of CCTV or other video data as part of a criminal invest ...Read More
Abstract:

SeeQuestor uses Deep Learning and Affordable Supercomputers to provide Radically Faster Video Intelligence to Police and Law Enforcement Agencies who need to search 100s or 1,000s of hours of CCTV or other video data as part of a criminal investigation or a search for a missing person. Developed with input from the Met Police and the British Transport Police, SeeQuestor is now in use by law enforcement agencies around the world. This session will focus on the technology used (Deep Learning and Affordable Super Computers, powered by GPUs), the academic pedigree (two leading computer vision research groups from the UK), and illustrate the capabilities of the SeeQuestor platform with examples drawn from real use cases.

  Back
 
Topics:
Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23492
Download:
Share:
 
Abstract:
Why does building AI Cities matter now for America? Why should the U.S. industry and government aggressively develop and deploy AI and deep learning to solve important problems around public safety and operational efficiency in our urban centers ...Read More
Abstract:

Why does building AI Cities matter now for America? Why should the U.S. industry and government aggressively develop and deploy AI and deep learning to solve important problems around public safety and operational efficiency in our urban centers? What are the global trends that make this the right time to drive these changes? We'll cover these topics and more.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7122
Download:
Share:
 
Abstract:
We'll explore how deep learning techniques can be used to transform passive surveillance systems into active threat-detection platforms for environments that range from retail, cities, and campuses. Deep Science is deploying deep learning so ...Read More
Abstract:

We'll explore how deep learning techniques can be used to transform passive surveillance systems into active threat-detection platforms for environments that range from retail, cities, and campuses. Deep Science is deploying deep learning solutions to spot robberies and assaults as they're occurring in real time.

  Back
 
Topics:
Intelligent Video Analytics, Cyber Security
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7123
Download:
Share:
 
Abstract:
Government agencies and commercial companies demonstrate high demand for versatile, stable, and highly efficient person identification solutions supporting cross-domain face recognition and person database clusterization in both controlled and u ...Read More
Abstract:

Government agencies and commercial companies demonstrate high demand for versatile, stable, and highly efficient person identification solutions supporting cross-domain face recognition and person database clusterization in both controlled and uncontrolled scenarios. Now it's possible to resolve cross-domain face recognition challenges using deep learning and even tasks of quadratic complexity using GPU-powered inference of CNN-based face recognition algorithms. We'll focus on (1) the concept of the GPU-powered platform for cross-domain face recognition; (2) its essential performance and critical technical characteristics; (3) an approach to reaching the demanded efficiency and quality by using the NVIDIA GPU; and (4) providing examples of completed and ongoing projects that demonstrate achieved high-performance and quality parameters in real-life conditions.

  Back
 
Topics:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning, Cyber Security, Leadership and Policy in AI
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7127
Download:
Share:
 
Abstract:
We'll explore how UMBO CV is leveraging deep learning techniques and GPUs to scale up how video is analyzed in real time and at enterprise scale.
 
Topics:
Intelligent Video Analytics, Cyber Security, Intelligent Machines, IoT & Robotics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7128
Download:
Share:
 
Abstract:
Body-worn cameras have proven to strengthen trust and accountability between law enforcement agencies and the communities they serve. However, large-scale use of body-worn cameras has generated massive amounts of data, which is practically impos ...Read More
Abstract:

Body-worn cameras have proven to strengthen trust and accountability between law enforcement agencies and the communities they serve. However, large-scale use of body-worn cameras has generated massive amounts of data, which is practically impossible for these agencies to use effectively. This has led to significant, and unproductive, time spent manually analyzing data. Axon Research is using the latest advances in deep learning and GPU acceleration to enable increased efficiency across the body-worn camera continuum by accelerating the many manual, time-consuming workflows in public safety, such as redacting footage in response to a public request. Attendees will hear the potential impact of large-scale deep learning on law enforcement and public safety information management.

  Back
 
Topics:
Intelligent Video Analytics, Cyber Security
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7142
Download:
Share:
 
Abstract:
In this talk, we will provide an overview of GPU based video dissemination architecture useful for distributing video across disadvantaged networks in a compute-constrained environment. This architecture is well suited for enabling machine learning a ...Read More
Abstract:
In this talk, we will provide an overview of GPU based video dissemination architecture useful for distributing video across disadvantaged networks in a compute-constrained environment. This architecture is well suited for enabling machine learning applications at the tactical edge. We will discuss the challenges that exist at the intersection of machine learning and video transcoding, specifically with regards to real-time object detection.  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7204
Download:
Share:
 
Abstract:
For security teams working to ensure public safety, the ability to minimize incident response time and speed forensic investigations is critical. We'll discuss a new end-to-end, deep learning, and GPU-reliant architecture and video search en ...Read More
Abstract:

For security teams working to ensure public safety, the ability to minimize incident response time and speed forensic investigations is critical. We'll discuss a new end-to-end, deep learning, and GPU-reliant architecture and video search engine for video data being deployed to solve this.

  Back
 
Topics:
Intelligent Video Analytics, Cyber Security
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7238
Download:
Share:
 
Abstract:
We'll showcase both the technology and use-cases for applying convolutional neural networks and GPUs to reverse the resolution-degrading effects of optical blur and sensor sampling, in order to reconstruct color video to nine times its captu ...Read More
Abstract:

We'll showcase both the technology and use-cases for applying convolutional neural networks and GPUs to reverse the resolution-degrading effects of optical blur and sensor sampling, in order to reconstruct color video to nine times its captured pixel density.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7250
Download:
Share:
 
Abstract:
We'll introduce the of the AI cities challenge winners announced at GTC2017. Honghui Shi from University of Illinois at Urbana-Champaign who will do a ten minute presentation on multiple-Kernel based vehicle tracking Using 3D deformable mode ...Read More
Abstract:

We'll introduce the of the AI cities challenge winners announced at GTC2017. Honghui Shi from University of Illinois at Urbana-Champaign who will do a ten minute presentation on multiple-Kernel based vehicle tracking Using 3D deformable models. Zheng Tang will then present on effective object detection from traffic camera videos.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7252
Download:
Share:
 
Abstract:
Recent advancements in drone technology and machine learning enabled PwC to enhance automatic analysis of photogrammetric and engineering documentation of a construction site. They trained a deep neural network to automatically identify features in a ...Read More
Abstract:
Recent advancements in drone technology and machine learning enabled PwC to enhance automatic analysis of photogrammetric and engineering documentation of a construction site. They trained a deep neural network to automatically identify features in aerial images and output a map of objects in the image such as asphalt, cars, and cement. This solution enhances construction progress monitoring, supports litigation and asset management, and provides a competitive edge with fast, scalable, and very accurate analytics. We'll discuss techniques and the main challenges of turning drone images into value.  Back
 
Topics:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning, Intelligent Machines, IoT & Robotics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7533
Download:
Share:
 
Abstract:
Miovision generates traffic analytics on over 16,000 hours of video every week from over 50 countries around the world using an NVIDIA GPU cloud-based system. Using surveillance-quality video, our system combines a deep convolutional neural network ( ...Read More
Abstract:
Miovision generates traffic analytics on over 16,000 hours of video every week from over 50 countries around the world using an NVIDIA GPU cloud-based system. Using surveillance-quality video, our system combines a deep convolutional neural network (CNN) with quality assurance agents, who review, verify, and correct, as needed, the CNN results. Using this hybrid approach, we're able to provide customers with accurate traffic analytics, such as traffic volume, class, and movements, and apply agent feedback to identify which real-world environmental conditions, lighting conditions, or perspectives contribute to CNN mislabeling or missed vehicles, pedestrians, or bicycles. Using the human corrections, Miovision can retrain the CNN to continuously improve its accuracy. We'll describe our traffic analytics pipeline and the use of sparse CNN representations to achieve robust state-of-the-art accuracy at faster than real-time performance.  Back
 
Topics:
Intelligent Video Analytics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7557
Download:
Share:
 
Abstract:
Through the application of artificial intelligence and deep learning, "computing at the edge" is changing how safety systems are detecting, capturing, analyzing, and applying reasoning to events. Using real-time analysis of the data fr ...Read More
Abstract:

Through the application of artificial intelligence and deep learning, "computing at the edge" is changing how safety systems are detecting, capturing, analyzing, and applying reasoning to events. Using real-time analysis of the data from cameras and inertial sensors mounted on a vehicle, we can not only detect unsafe driving events but also analyze the chain of events that lead to unsafe situations. We can recognize driver's positive performance in addition to areas where best practices need to be reinforced. Power-efficient and powerful deep learning processors enable us to process all of this data in real time at the edge of the network. This allows us to create an accurate and comprehensive record of driving performance that fleet managers can use to create incentives for safer driving. Insurance companies can also use this information to set proper premiums customized for individual drivers and potentially adjusted dynamically to reflect the driving environment. 

  Back
 
Topics:
Intelligent Video Analytics, Autonomous Vehicles, Federal, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7661
Download:
Share:
 
Abstract:
The potential information buried in sensors is enormous. There is far too much data from sensors to all be actively monitored and managed by agents. Large-scale autonomous monitoring systems require a significant amount of computing resources. Manual ...Read More
Abstract:
The potential information buried in sensors is enormous. There is far too much data from sensors to all be actively monitored and managed by agents. Large-scale autonomous monitoring systems require a significant amount of computing resources. Manual configuring of sensors to detect specific activities can be time consuming. Correlating and fusing different sensor modalities in real time for co-presence for anomaly could be computationally intractable. We'll demonstrate how the Omni AI platform uses NVIDIA GPUs to enable high-performance and high-scalability real-time anomaly detection on thousands of sensors using an unsupervised online machine learning engine with the neuro-linguistic cognitive model.  Back
 
Topics:
Intelligent Video Analytics, Accelerated Data Science, Intelligent Machines, IoT & Robotics, Federal, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7200
Download:
Share:
 
Abstract:
Today, billions of sensors gathering zettabytes of data are offering organizations a treasure trove of information that can help them better serve their customer needs. With the advances of 5G infrastructure, companies now have the ability to br ...Read More
Abstract:

Today, billions of sensors gathering zettabytes of data are offering organizations a treasure trove of information that can help them better serve their customer needs. With the advances of 5G infrastructure, companies now have the ability to bring AI models to the edge, where the data is generated and real-time decisions need to be made. Kubernetes eliminates many of the manual processes involved in deploying, managing and scaling applications, and is becoming a standard for deployment from the data center to the edge. NVIDIA NGC product and engineering experts will walk through the latest enhancements to its GPU-accelerated software hub, and demonstrate how NVIDIA is facilitating the deployment and management of AI applications at the edge.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
MWC
Year:
2019
Session ID:
mwcla905
Streaming:
Share:
 
Speakers:
Abstract:
In this talk, you will learn how NVIDIA GPUs allow AiFi's auto-checkout system to achieve accuracy and efficiency in in-store customer tracking, shelf inventory management, and automated store monitoring.
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
MWC
Year:
2019
Session ID:
mwcla906
Streaming:
Download:
Share:
 
Abstract:
A revolutionary deep data analytics platform for retailers, learn how AnyVision Insights can help you gain an end-to-end, accurate view of your stores daily operation, customers journey, shopping patterns and sales funnel. A live demo will illus ...Read More
Abstract:

A revolutionary deep data analytics platform for retailers, learn how AnyVision Insights can help you gain an end-to-end, accurate view of your stores daily operation, customers journey, shopping patterns and sales funnel. A live demo will illustrate Insights vast capabilities through its cutting-edge recognition platform specially designed for real-world retailers, including unique people counting, heat and path mapping, focus of attention, duration in store, bounce rate, rush hours, demographics classification, VIP recognition, zone breakdown, and more.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
MWC
Year:
2019
Session ID:
mwcla911
Streaming:
Download:
Share:
 
Abstract:
This session will give an overview on the performance and efficiency of running the Malong RetailAI® software stack on Dell EMC PowerEdge R7425 server for retail analytics. The objective is to show how the stack can deliver high throughput & ...Read More
Abstract:

This session will give an overview on the performance and efficiency of running the Malong RetailAI® software stack on Dell EMC PowerEdge R7425 server for retail analytics. The objective is to show how the stack can deliver high throughput & low latency inferencing performance on Nvidia T4 GPU. We will look into some of the use cases that can be solved by running the algorithms developed by Malong in the area of product recognition. We will talk about Curriculum Net which is based on weakly supervised learning and how these algorithms are being run on Nvidia T4 GPU by taking advantage of TensorRT. The attendee will also get an understanding on how we take advantage of AMD CPU to deliver a higher throughput low latency solution. By taking advantage of multiple PCIe lanes we can provide a true scale-up intelligent video analytics solution with T4 GPU.

  Back
 
Topics:
Intelligent Video Analytics
Type:
Talk
Event:
MWC
Year:
2019
Session ID:
mwcla924
Streaming:
Download:
Share:
 
Abstract:
Well discuss our company, CrowdAI, and how it can provide reliable data in the aftermath of a natural disaster. By coupling advanced AI techniques with satellite, aerial, and drone imagery and video, CrowdAI hopes to better analyze risk-prone areas b ...Read More
Abstract:
Well discuss our company, CrowdAI, and how it can provide reliable data in the aftermath of a natural disaster. By coupling advanced AI techniques with satellite, aerial, and drone imagery and video, CrowdAI hopes to better analyze risk-prone areas before a natural disaster. We can then equip decision-makers with more accurate and timely data after the event occurs.  Back
 
Topics:
AI & Deep Learning Research, Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91318
Download:
Share:
 
Abstract:
Well explain why performing near real-time inference on live video streams is difficult but critical for national security agencies, which require accurate information as quickly as possible. By combining the scale and agility of AWS with NVIDIA tech ...Read More
Abstract:
Well explain why performing near real-time inference on live video streams is difficult but critical for national security agencies, which require accurate information as quickly as possible. By combining the scale and agility of AWS with NVIDIA technology, agencies can build AI applications that solve tough, mission-critical problems to strengthen national security and the nation. AWS and NVIDIA have built an innovative workflow to perform inference and analytics on videos by leveraging NVIDIA DeepStream SDK; the new AWS G4 instance type; and additional AWS services. Well demonstrate how AWS and NVIDIA are delivering new technologies that are applicable to a wide range of mission use cases. Well also showcase a video inference pipeline on a live video stream in near real-time.  Back
 
Topics:
Cyber Security, Intelligent Video Analytics
Type:
Sponsored Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91466
Download:
Share:
 
Abstract:
Well discuss various edge computing use cases in industrial IoT across verticals such as manufacturing, fuel, smart buildings, etc. Well demonstrate the value of edge computing and explain why video content analysis is the poster child for edge intel ...Read More
Abstract:
Well discuss various edge computing use cases in industrial IoT across verticals such as manufacturing, fuel, smart buildings, etc. Well demonstrate the value of edge computing and explain why video content analysis is the poster child for edge intelligence. From there, well present a specific use case deployed in the oil and gas sector, and discuss the division of labor between CPUs and GPUs, especially as it pertains to the enablement of sensor fusion technology.  Back
 
Topics:
Intelligent Machines, IoT & Robotics, Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91198
Download:
Share:
 
Abstract:
Well discuss convolutional neural networks (CNNs), which have recently become the preferred tool for many visual detection tasks including object classification, localization, detection, and segmentation. CNNs are specialized neural networks composed ...Read More
Abstract:
Well discuss convolutional neural networks (CNNs), which have recently become the preferred tool for many visual detection tasks including object classification, localization, detection, and segmentation. CNNs are specialized neural networks composed of many layers and specifically designed to analyze grid-like data like images. One of their key features is the ability to automatically detect important features within an image such as edges, patterns, and shapes. Previously, these features had to be manually engineered by subject matter experts. Inspired by the significant achievements CNNs have experienced in computer vision, well examine U-Net, a specific CNN architecture, which is suited for visual defect detection. Well identify situations for the use of this architecture for external defect detection on aircrafts, and experimentally discuss its performance across a dataset of common visual defects.  Back
 
Topics:
AI & Deep Learning Research, Intelligent Video Analytics
Type:
Sponsored Talk
Event:
GTC Washington D.C.
Year:
2019
Session ID:
DC91241
Download:
Share:
 
Abstract:
We'll discuss how Motionloft uses advanced computer vision at the edge to help retailers increase customer satisfaction and revenue. Our sensors, convolutional neural networks, and NVIDIA GPUs allow retailers to analyze movements of people i ...Read More
Abstract:

We'll discuss how Motionloft uses advanced computer vision at the edge to help retailers increase customer satisfaction and revenue. Our sensors, convolutional neural networks, and NVIDIA GPUs allow retailers to analyze movements of people inside stores, and turn these movements into actionable insights. We'll explain how our technology can monitor and better understand the impact of factors like long lines, which cost retailers $15.8 billion in lost sales annually. In the past, this sort of measurement could only be done with handheld clickers. We'll also cover how retailers can track other elements that affect the customer experience including store occupancy, service transaction times, service-area patronage, and customer abandonment.

  Back
 
Topics:
Consumer Engagement & Personalization, Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9324
Streaming:
Download:
Share:
 
Abstract:
Learn how to develop faster, scalable, and better GPU-Accelerated distributed inference on multi-node and multi-GPU cluster environments. In most of the benchmark cases, linear scalability for throughput performance is not guaranteed with increasing ...Read More
Abstract:
Learn how to develop faster, scalable, and better GPU-Accelerated distributed inference on multi-node and multi-GPU cluster environments. In most of the benchmark cases, linear scalability for throughput performance is not guaranteed with increasing the number of GPUs and servers. We'll discuss present an efficient scale-out method for deploying deep learning-based object detection models on multi-node and multi-GPU clusters using Apache Hadoop and Spark. We'll explain how to deploy 120 deep learning models (YOLOv2) on our own video datasets with NVIDIA Tesla M60 GPU (30EA) Hadoop cluster. Our approach achieved about 20 percent faster inference throughput with super-linear scalability from one GPU server to 30 GPU cluster. This session will be a combination of lecture and videos about our GPU-Accelerated distributed inference platform for large-scale streaming data analytics.  Back
 
Topics:
AI Application, Deployment & Inference, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9343
Streaming:
Download:
Share:
 
Abstract:
Artificial intelligence and the latest in computer vision techniques are quickly re-shaping the future of retail. By deploying modern deep learning techniques, technology companies are improving the overall retail shopping experience by getting ...Read More
Abstract:

Artificial intelligence and the latest in computer vision techniques are quickly re-shaping the future of retail. By deploying modern deep learning techniques, technology companies are improving the overall retail shopping experience by getting rid of slow, cumbersome checkout lines. We'll talk about our work on autonomous checkout, which can make shopping a seamless, magical and more human interaction. Standard Cognition, along with other technology innovators like AmazonGo, have announced plans to deploy thousands of autonomous checkout-enabled retail stores by 2021.

  Back
 
Topics:
Consumer Engagement & Personalization, Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9404
Streaming:
Download:
Share:
 
Abstract:
We'll talk about applying an LSTM-based trajectory forecasting framework to the problem of construction workers and equipment safety management, a problem with applications to activity forecasting, AEC industries, and AI smart cities. Our talk will ...Read More
Abstract:
We'll talk about applying an LSTM-based trajectory forecasting framework to the problem of construction workers and equipment safety management, a problem with applications to activity forecasting, AEC industries, and AI smart cities. Our talk will provide an overview of construction safety management, construction site visual data collection and pre-processing, and forecasting model architecture. We'll discuss our rationale for designing a final model based on characteristics of construction data, and show experimental results as well as ablation study results. We'll also show a demo or video of our safety-management software.  Back
 
Topics:
Product & Building Design, Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9424
Streaming:
Download:
Share:
 
Abstract:
This talk will focus on latest updates of NVIDIA video technologies such as video encoding, decoding and optical flow SDK, with particular emphasis on quality, performance and functionality improvements brought by Turing architecture. We will also di ...Read More
Abstract:
This talk will focus on latest updates of NVIDIA video technologies such as video encoding, decoding and optical flow SDK, with particular emphasis on quality, performance and functionality improvements brought by Turing architecture. We will also discuss applications of the video technologies into various DL/AI use cases and optimization techniques in such use cases. A new release of the video SDK (9.0) and the first version of Optical Flow SDK (1.0) are set to launch in Q1 2019, so this session will be an ideal preview.  Back
 
Topics:
Video & Image Processing, Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9331
Streaming:
Download:
Share:
 
Abstract:
This session proposes a simple but robust method of data distribution for large-scale IoT deployments. Attendees will learn how to use a peer-peer publish/subscribe messaging technology based on data topics to facilitate collection of initial in ...Read More
Abstract:

This session proposes a simple but robust method of data distribution for large-scale IoT deployments. Attendees will learn how to use a peer-peer publish/subscribe messaging technology based on data topics to facilitate collection of initial in-situ data, distribution of inferencing models, load-sharing between "worker nodes", collation of inferencing results from many nodes to a central "command", and collation of corner-case data to facilitate iterative updates to the trained model.

  Back
 
Topics:
Intelligent Machines, IoT & Robotics, Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8307
Streaming:
Download:
Share:
 
Abstract:
Designing an autonomous machine are about much more than just the AI. Electrical, Mechanical, Connectivity, and Security are just a few of the disciplines where you will require expertise. Not all companies will have complete expertise in all th ...Read More
Abstract:

Designing an autonomous machine are about much more than just the AI. Electrical, Mechanical, Connectivity, and Security are just a few of the disciplines where you will require expertise. Not all companies will have complete expertise in all these areas. In this session, we will provide examples followed by design considerations, strategies and solutions to begin to address these challenges.

  Back
 
Topics:
Intelligent Machines, IoT & Robotics, Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2018
Session ID:
E8522
Streaming:
Download:
Share:
 
Abstract:
Learn how VisionLabs GPU-powered solutions contribute to creating a safer, smarter Megacity a metropolitan area with a total population in excess of ten million people. We'll do a deep dive into three implemented and ongoing huge scale smart ...Read More
Abstract:

Learn how VisionLabs GPU-powered solutions contribute to creating a safer, smarter Megacity a metropolitan area with a total population in excess of ten million people. We'll do a deep dive into three implemented and ongoing huge scale smart-city projects, understand challenges, technical specifics and how GPU computing impacts each of these cases: Face authentication-based immobilizer and driver monitoring systems for municipal service vehicles powered by the NVIDIA Jetson TX2 embedded platform; Megacity scale vehicle traffic analysis and anomalies detection powered by NVIDIA Tesla P40 with over 80 million daily recognition requests; National scale face identification platform for financial services with over 110 million faces in its database. The foundation of all these projects is VisionLabs LUNA a cross-platform object recognition software based on proprietary deep neural networks (DNN) inference framework. To build cost-effective solutions, VisionLabs use know-hows in DNN quantization and acceleration. In terms of accuracy, VisionLabs is recognized as a top three best in the world by National Institute of Standards and Technology's face recognition vendor test, and LFW by University of Massachusetts challenges.

  Back
 
Topics:
AI Application, Deployment & Inference, AI Startup, Intelligent Video Analytics, Deep Learning & AI Frameworks, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8584
Streaming:
Download:
Share:
 
Abstract:
Miovision presents a video-based traffic analytics system, capable of tracking and classifying vehicles in real time throughout cities. The system leverages Jetson TX2 modules and inferencing to accurately classify vehicles at over 50 frames per ...Read More
Abstract:

Miovision presents a video-based traffic analytics system, capable of tracking and classifying vehicles in real time throughout cities. The system leverages Jetson TX2 modules and inferencing to accurately classify vehicles at over 50 frames per second using single-shot multibox detection and DAC, a VGG-based network. We'll cover many of the issues our teams went through to design and implement the system, including data collection, annotation, training, incorporating continuous training, and deep learning iteration. We'll also illustrate how the measured traffic trends were used to reduce congestion and evaluate the health of traffic corridors.

  Back
 
Topics:
Computer Vision, Intelligent Video Analytics, Intelligent Machines, IoT & Robotics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8383
Streaming:
Download:
Share:
 
Abstract:
Every law enforcement agency receives tens if not hundreds of suspected child abuse cases every month. Each case may contain one or more hard disks and/or other storage media. On average, each hard disk contains about 200,000 images and hundreds of h ...Read More
Abstract:
Every law enforcement agency receives tens if not hundreds of suspected child abuse cases every month. Each case may contain one or more hard disks and/or other storage media. On average, each hard disk contains about 200,000 images and hundreds of hours of video recordings. To successfully prosecute the offenders, every one of those images/videos needs to be correctly graded to help the courts assess the level of the offence. Even though many simple tools are used to accelerate this laborious process, every case can take hours if not days to prepare. This puts a significant strain on law enforcement worldwide. At this scale, the process is also very error prone, where evidence can be missed or ignored. Hail-O platform, which is the primary focus of this talk, rapidly inspects all images and videos detected on the disk of the offender, and using artificial intelligence automatically detects and grades indecent images of children. The adaptation of Hail-O allows law enforcement agencies to significantly reduce the workload required in prosecuting offenders and, at the same time, ensuring the consistency of the grading process. Hail-O will reduce law enforcement workload.  Back
 
Topics:
GIS, Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8613
Streaming:
Download:
Share:
 
Abstract:
A wide area and city surveillance system solution for running real-time video analytics on thousands of 1080p video streams will be presented. System hardware is an embedded computer cluster based on NVIDIA TX1/TX2 and NXP iMX6 modules. A custom ...Read More
Abstract:

A wide area and city surveillance system solution for running real-time video analytics on thousands of 1080p video streams will be presented. System hardware is an embedded computer cluster based on NVIDIA TX1/TX2 and NXP iMX6 modules. A custom designed system software manages job distribution, resulting in collection and system wide diagnostics including instantaneous voltage, power and temperature readings. System is fully integrated with a custom designed video management software, IP cameras and network video recorders. Instead of drawing algorithm results on the processed video frames, re-encoding and streaming back to the operator computer for display, only the obtained metadata is sent to the operator computer. Video management software streams video sources independently, and synchronizes decoded video frames with the corresponding metadata locally, before presenting the processed frames to the operator.

  Back
 
Topics:
AI Application, Deployment & Inference, Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8409
Streaming:
Download:
Share:
 
Abstract:
During this presentation we will review a deep neural network architecture and its training approaches used for producing high volume of estimations of travel times on a road graph with historical routes and traffic. This includes initial and continu ...Read More
Abstract:
During this presentation we will review a deep neural network architecture and its training approaches used for producing high volume of estimations of travel times on a road graph with historical routes and traffic. This includes initial and continuous online training, finding various sources to produce training data, challenges of quality control, and, of course, the invaluable role of GPU's for computation during both training and inference.  Back
 
Topics:
AI & Deep Learning Research, Product & Building Design, Intelligent Video Analytics, GIS, Autonomous Vehicles
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8156
Streaming:
Download:
Share:
 
Abstract:
We'll explore new techniques for TV show summarization using multimodal deep learning for saliency detection and fusion. For TV show summarization, the goal is to compact visual summary with informativeness and enjoyability to attract audience. In o ...Read More
Abstract:
We'll explore new techniques for TV show summarization using multimodal deep learning for saliency detection and fusion. For TV show summarization, the goal is to compact visual summary with informativeness and enjoyability to attract audience. In our work, we propose a multimodal summarization platform to integrate the multimodal saliences learned from video, audio, and text. Our work focuses on three aspects: 1) the saliency extraction for video, audio, and text using deep learning networks; 2) fusion framework design for multimodal information integration; 3) developing tools to speed up video processing. Using AI Vision, which is a public cloud-based AI service, we summarize a TV show with 11 hours duration in one minute.  Back
 
Topics:
Computer Vision, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8221
Streaming:
Share:
 
Abstract:
Robust object tracking requires knowledge and understanding of the object being tracked: its appearance, motion, and change over time. A tracker must be able to modify its underlying model and adapt to new observations. We present Re3, a real-ti ...Read More
Abstract:

Robust object tracking requires knowledge and understanding of the object being tracked: its appearance, motion, and change over time. A tracker must be able to modify its underlying model and adapt to new observations. We present Re3, a real-time deep object tracker capable of incorporating temporal information into its model. Rather than focusing on a limited set of objects or training a model at test-time to track a specific instance, we pretrain our generic tracker on a large variety of objects and efficiently update on the fly; Re3 simultaneously tracks and updates the appearance model with a single forward pass. This lightweight model is capable of tracking objects at 150 FPS, while attaining competitive results on challenging benchmarks. We also show that our method handles temporary occlusion better than other comparable trackers using experiments that directly measure performance on sequences with occlusion.

  Back
 
Topics:
AI & Deep Learning Research, Intelligent Video Analytics, Intelligent Machines, IoT & Robotics, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8298
Streaming:
Share:
 
Abstract:
There is a clear opportunity for retailers to generate loyalty and increase sales by focusing on the overall customer experience. We'll describe how we are developing solutions to track customer activity and build profiles based on physical store ac ...Read More
Abstract:
There is a clear opportunity for retailers to generate loyalty and increase sales by focusing on the overall customer experience. We'll describe how we are developing solutions to track customer activity and build profiles based on physical store activity to personalize the in-store shopping experience. We'll also describe how GPUs and deep learning are used to create these capabilities ? all while protecting personal information and privacy.  Back
 
Topics:
Accelerated Data Science, Intelligent Video Analytics, Data Center & Cloud Infrastructure, Consumer Engagement & Personalization, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8144
Streaming:
Share:
 
Abstract:
We''ll present a framework that can learn a compute-intensive deep neural networks (DNNs) task using multiple AI blocks and evolve better confidence by combining estimates. We''ll consider the example of establishing the identity of a user using spee ...Read More
Abstract:
We''ll present a framework that can learn a compute-intensive deep neural networks (DNNs) task using multiple AI blocks and evolve better confidence by combining estimates. We''ll consider the example of establishing the identity of a user using speech and image data. The system consists of two blocks - the AI block and Arbiter block. The AI block uses multiple DNNs (voice-based and image-based DNNs that generate a low confidence estimate initially). These AI blocks assist each other using Arbiter blocks and build confidence, improve accuracy, and learn salient features over time. Arbiter can store recent unacquainted data at run time in noisy and distorted environments and train the AI blocks periodically or on an on-demand basis. This concept could potentially improve the automatic speech recognition capabilities and allow detection of faces even when variable features of faces change with time. The GPU is the ideal choice as the task requires inferencing as well as training on the go.  Back
 
Topics:
AI & Deep Learning Research, Intelligent Video Analytics, Advanced AI Learning Techniques
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8331
Streaming:
Download:
Share:
 
Abstract:
Go beyond working with a single sensor and enter the realm of Intelligent Multi-Sensor Analytics (IMSA). We''ll introduce concepts and methods for using deep learning with multi-sensor, or heterogenous, data. There are many resources and ...Read More
Abstract:

Go beyond working with a single sensor and enter the realm of Intelligent Multi-Sensor Analytics (IMSA). We''ll introduce concepts and methods for using deep learning with multi-sensor, or heterogenous, data. There are many resources and examples available for learning how to leverage deep learning with public imagery datasets. However, few resources exist to demonstrate how to combine and use these techniques to process multi-sensor data. As an example, we''ll introduce some basic methods for using deep learning to process radio frequency (RF) signals and make it a part of your intelligent video analytics solutions. We''ll also introduce methods for adapting existing deep learning frameworks for multiple sensor signal types (for example, RF, acoustic, and radar). We''ll share multiple use cases and examples for leveraging IMSA in smart city, telecommunications, and security applications.

  Back
 
Topics:
AI & Deep Learning Research, Intelligent Video Analytics, Intelligent Machines, IoT & Robotics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8260
Streaming:
Download:
Share:
 
Abstract:
In this talk we will discuss the work Columbia University, in partnership with NYC government, is using deep learning and GPUs to develop smart city traffic management facilitating support for navigation/movement of multitude of vehicles (including a ...Read More
Abstract:
In this talk we will discuss the work Columbia University, in partnership with NYC government, is using deep learning and GPUs to develop smart city traffic management facilitating support for navigation/movement of multitude of vehicles (including autonomous cars) in dense urban environments with many pedestrians. We will describe our work in real-time tracking of cars and pedestrians, prediction of movement based on historical observations of the intersection, backed by ultra-low latency wireless communications and edge computing nodes.  Back
 
Topics:
AI & Deep Learning Research, Intelligent Video Analytics, Autonomous Vehicles
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8201
Streaming:
Share:
 
Abstract:
Training AI agents that can successfully generalize requires large amounts of diverse labeled training data. Collecting and labeling data is a significant cost in the development of AI applications, which, in some cases, may not even be feasib ...Read More
Abstract:
Training AI agents that can successfully generalize requires large amounts of diverse labeled training data. Collecting and labeling data is a significant cost in the development of AI applications, which, in some cases, may not even be feasible. We'll describe computer graphics facial models that we are developing to generate large labeled synthetic facial data for training deep neural networks. Facial analysis is central to many vision applications that involve human-computer interaction, including robotics, autonomous cars, rehabilitation, and extended usability. Generating and animating human faces with high realism is a well-studied problem in computer graphics; however, very few computer vision AI techniques take advantage of rendered facial data to augment or replace manually collected training data. We'll share key insights of how we successfully use synthetic facial data for training facial analysis classifiers. We'll also demonstrate many sub-tasks on which synthetic data helps to significantly improve accuracy and reduces the need for manual data collection.
 
  Back
 
Topics:
AI & Deep Learning Research, Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8794
Streaming:
Share:
 
Keynote (Keynote Talk)
Abstract:
Don't miss this keynote from NVIDIA Founder & CEO, Jensen Huang, as he speaks on the future of computing. 
 
Topics:
Artificial Intelligence and Deep Learning, Virtual Reality & Augmented Reality, Data Center & Cloud Infrastructure, Autonomous Vehicles, Intelligent Video Analytics
Type:
Keynote
Event:
GTC Israel
Year:
2017
Session ID:
SIL7001
Streaming:
Share:
 
Abstract:
Modern computing hardware and NVIDIA Jetson TX1 / TX2 performance create new possibilities for drones and enable autonomous AI systems, where image processing can be done on-board during flight or near the camera. We'll present how PIXEVIA s ...Read More
Abstract:

Modern computing hardware and NVIDIA Jetson TX1 / TX2 performance create new possibilities for drones and enable autonomous AI systems, where image processing can be done on-board during flight or near the camera. We'll present how PIXEVIA system covers vision processing and AI tasks for drones, e.g., image stabilization, position estimation, object detection, tracking, and classification using deep neural networks, and self-evolvement after deployment. We'll describe software frameworks Caffe/Tensorflow with cuDNN, VisionWorks, and NVIDIA CUDA to achieve real-time vision processing and object recognition. Real-world use cases with drone manufacturers Aerialtronics and Squadrons Systems, and with smart city applications in Vilnius and Tallinn will be presented during this talk.

  Back
 
Topics:
Intelligent Machines, IoT & Robotics, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23320
Download:
Share:
 
Abstract:
Image recognition identifies one or more people in images or videos by analyzing and comparing patterns. Algorithms for face recognition typically extract facial features and compare them to a database to find the best match. This system may be used ...Read More
Abstract:
Image recognition identifies one or more people in images or videos by analyzing and comparing patterns. Algorithms for face recognition typically extract facial features and compare them to a database to find the best match. This system may be used in biometric, security, and surveillance systems, but is also useful in the social media space where personal affinities can be applied upon successful identification. The infrastructure to support the training and building phases of this application requires a large amount of data to be processed in parallel.  Back
 
Topics:
Computer Vision, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23070
Download:
Share:
 
Abstract:
We present a novel unsupervised method for face identity learning from video sequences. The method exploits Convolutional Neural Networks for face detection and face description together with a smart learning mechanism that exploits the temporal ...Read More
Abstract:

We present a novel unsupervised method for face identity learning from video sequences. The method exploits Convolutional Neural Networks for face detection and face description together with a smart learning mechanism that exploits the temporal coherence of visual data in video streams. We introduce a novel feature matching solution based on Reverse Nearest Neighbour and a feature forgetting strategy that supports incremental learning with memory size control, while time progresses. It is shown that the proposed learning procedure is asymptotically stable and can be effectively applied to relevant applications like multiple face tracking and online open world face recognition from video streams. The whole system including the smart incremental learning mechanism take advantage of the GPU.

  Back
 
Topics:
Computer Vision, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23202
Download:
Share:
 
Abstract:
Computer Vision with CNNs performs well for people detection. This is not enough. A step forward can be taken to understand the aspect of people detected in low resolution, or corrupted by occlusions in the crowd; to track them in the wild; to d ...Read More
Abstract:

Computer Vision with CNNs performs well for people detection. This is not enough. A step forward can be taken to understand the aspect of people detected in low resolution, or corrupted by occlusions in the crowd; to track them in the wild; to detect saliency and pay attention to details only; to forecast motion and human actions. The next solutions will be provided by new neural architectures based on autoencoders and recurrent architectures, such as Generative Adversarial Networks and Long Short Term Memories. The session will present how they work, how they can be implemented on GPUs and how they are used in real applications, such as in AI cities form static and moving cameras and in collaborative environments.

  Back
 
Topics:
Computer Vision, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23267
Download:
Share:
 
Abstract:
In this talk, I will highlight the main research challenges facing the field of activity detection in untrimmed videos, as well as, deep learning based methods developed at KAUST to address them. Massive amounts of video data need to be processe ...Read More
Abstract:

In this talk, I will highlight the main research challenges facing the field of activity detection in untrimmed videos, as well as, deep learning based methods developed at KAUST to address them. Massive amounts of video data need to be processed for relevant semantic information that predominantly focuses on human activities (i.e. single human, human-to-human, and human-to-object interactions). While this problem is encountered in many real-world applications (e.g. video surveillance, large-scale video summarization, and ad placement in video platforms), automated vision solutions have been hindered by several challenges including the lack of large-scale datasets for learning and the need for real-time processing. I will highlight how deep learning can be used to tackle these challenges.

  Back
 
Topics:
Computer Vision, Intelligent Video Analytics
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23312
Download:
Share:
 
Abstract:
Learn how deep learning is used to process video streams to analyse human behaviour in real-time. We will detail our solution to recognise fine-grained movement patterns of people how they perform everyday actions like e.g. walking, eating, shak ...Read More
Abstract:

Learn how deep learning is used to process video streams to analyse human behaviour in real-time. We will detail our solution to recognise fine-grained movement patterns of people how they perform everyday actions like e.g. walking, eating, shaking hands, talking to each other. The novelty of our technical solution is that our system learns these capabilities from watching lots of video snippets showing such actions. This is exciting because very different applications can be realised with the same algorithms as we follow a purely data-driven, machine learning approach. We will explain what new types of deep neural networks we created and how we employ our Crowd Acting (tm) platform to cost-efficiently acquire hundred thousands videos for that.

  Back
 
Topics:
Autonomous Vehicles, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23233
Download:
Share:
 
Abstract:
Government agencies and commercial companies today demonstrate high demand to versatile, stable and highly-efficient person identification solutions supporting cross-domain face recognition and person database clusterization in both controlled a ...Read More
Abstract:

Government agencies and commercial companies today demonstrate high demand to versatile, stable and highly-efficient person identification solutions supporting cross-domain face recognition and person database clusterization in both controlled and uncontrolled scenarios. Now it becomes possible to successfully resolve cross-domain face recognition challenge using deep learning and even tasks of quadratic complexity using GPU-powered inference of CNN-based face recognition algorithms. We''ll focus on (I) the concept of the GPU-powered platform for cross-domain face recognition; (II) its essential performance and critical technical characteristics; (III) reaching required accuracy and performance by using NVIDIA GPUs; (IV) examples of completed and ongoing face recognition projects

  Back
 
Topics:
Computer Vision, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23331
Download:
Share:
 
Abstract:
We present a face recognition system that can recognize multiple persons parallel in real-time running on a single Jetson TX2. Due to rapid progress in deep learning accuracy of face recognition has surpassed human level recently. GPUs became th ...Read More
Abstract:

We present a face recognition system that can recognize multiple persons parallel in real-time running on a single Jetson TX2. Due to rapid progress in deep learning accuracy of face recognition has surpassed human level recently. GPUs became the major platform to train and run deep learning models. Speed of NVidia GPUs on deep learning tasks is increasing rapidly due to hardware and software optimizations. We present a system that combines the most accurate face detection and recognition models with the fastest software stack. Combined with a 4K camera the system can recognize over 10 persons parallel in crowd situations even from 10 meter range. The system can be deployed to low power embedded environments such as drones.

  Back
 
Topics:
Intelligent Machines, IoT & Robotics, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23445
Download:
Share:
 
Abstract:
Using cutting-edge AI technologies, self-driving cars have the potential to significantly reduce traffic fatalities, improve transportation mobility and accessibility, and increase productivity. To realize the promise of these many benefits, pub ...Read More
Abstract:

Using cutting-edge AI technologies, self-driving cars have the potential to significantly reduce traffic fatalities, improve transportation mobility and accessibility, and increase productivity. To realize the promise of these many benefits, public policy must allow innovation to flourish by, for example, removing barriers to testing and clarifying state and federal regulatory authority. During this panel, we'll hear from top policymakers and industry representatives on what key policies need to be enacted to advance the deployment of self-driving cars, and how all stakeholders are working together to further that goal.

  Back
 
Topics:
Leadership and Policy in AI, Intelligent Video Analytics, Autonomous Vehicles
Type:
Panel
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7158
Download:
Share:
 
Abstract:
We'll discuss practical applications of state-of-the-art convolutional neural networks (CNNs) to the challenges of surveillance systems. We'll discuss modifications to a current state-of-the-art neural network to improve detection of small targets ...Read More
Abstract:
We'll discuss practical applications of state-of-the-art convolutional neural networks (CNNs) to the challenges of surveillance systems. We'll discuss modifications to a current state-of-the-art neural network to improve detection of small targets while maintaining detection performance on larger targets. We'll then discuss a novel sensor-fusion method to improve small target localization and provide track classification to a fused common operating picture. We'll present results from the MS-COCO dataset and from data collected on our own testbed, which recorded small quadcopters in flight using a commercial surveillance camera. Finally, we'll discuss how our novel CNN detection and sensor fusion algorithms can be used to enable surveillance security applications. Sponsor: DHS S&T.  Back
 
Topics:
Cyber Security, Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7180
Download:
Share:
 
Abstract:
We'll introduce DeepStream, NVIDIA's solution for high-performance video analytics. One of the grand challenges of AI is to understand video content. Applications are endless: video surveillance, live video streaming, ad placement, and m ...Read More
Abstract:

We'll introduce DeepStream, NVIDIA's solution for high-performance video analytics. One of the grand challenges of AI is to understand video content. Applications are endless: video surveillance, live video streaming, ad placement, and more. The problem is that deep learning, which has been boosting modern AI, is computationally expensive. It's even more challenging when it comes to live stream video. That's why we're building the NVIDIA DeepStream SDK, which simplifies development of high-performance video analytics applications powered by deep learning. It's built on top of the NVIDIA Video SDK, which can leverage the GPU's hardware encoding and decoding horsepower, and on top of NVIDIA TensorRT, which accelerates deep neural network's inferencing. We have seen successful large-scale deployment of such intelligent video analytics systems, and we see this as an unstoppable trend.

  Back
 
Topics:
Developer Tools, Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7198
Download:
Share:
 
Abstract:
This talk is a lightning introduction to object detection and image segmentation for data scientists, engineers, and technical professionals. This task of computer-based image understanding underpins many major fields such as autonomous driving, ...Read More
Abstract:

This talk is a lightning introduction to object detection and image segmentation for data scientists, engineers, and technical professionals. This task of computer-based image understanding underpins many major fields such as autonomous driving, smart cities, healthcare, national defense, and robotics. Ultimately, the goals of this talk are to provide a broad context and clear roadmap from traditional computer vision techniques to the most recent state-of-the-art methods based on deep learning and convolution neural networks (CNNs). Additional considerations for network deployment at the edge or on the road in an autonomous vehicle using NVIDIA's latest TensorRT release will be discussed.

  Back
 
Topics:
Autonomous Vehicles, Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7217
Download:
Share:
 
Abstract:
Our cities are increasingly challenged to bring intelligence and safety to their citizens' lives. New technologies using AI are promising to change the way cities operate. How will citizens benefit? What are the policies and investments nece ...Read More
Abstract:

Our cities are increasingly challenged to bring intelligence and safety to their citizens' lives. New technologies using AI are promising to change the way cities operate. How will citizens benefit? What are the policies and investments necessary to bring this about as soon as possible?

  Back
 
Topics:
Leadership and Policy in AI, Intelligent Video Analytics
Type:
Panel
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7226
Download:
Share:
 
Abstract:
The rapid deployment of video sensors across multiple platforms, such as security cameras, unmanned aerial vehicles, and satellites, has resulted in information overload, outpacing analyst ability to effectively use the capability. State-of-the-art p ...Read More
Abstract:
The rapid deployment of video sensors across multiple platforms, such as security cameras, unmanned aerial vehicles, and satellites, has resulted in information overload, outpacing analyst ability to effectively use the capability. State-of-the-art processing, exploitation, and dissemination systems primarily focus on forensic use of stored video for identification and tracking of objects and subjects of interest. Not many capabilities exist to deploy and monitor in real-time 100s and 1,000s sensors in cities, bases, airports, and similar venues. Using cloud deep learning services or APIs (for example, Amazon Rekognition) is not only cost prohibitive, but also presents challenges to organizations with sensitive or classified data. We'll discuss various efforts at the Johns Hopkins University Applied Physics Laboratory to develop inexpensive, low size, weight, and power (SWaP) real-time automatic target recognition systems.  Back
 
Topics:
Computer Vision, Intelligent Video Analytics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7233
Download:
Share:
 
Abstract:
Learn an effective strategy for training deep video captioning and semantic search of overhead scenes, taking advantage of the photo-realism and ubiquitous access to high-level semantic information in a game like Grand Theft Auto. We train video capt ...Read More
Abstract:
Learn an effective strategy for training deep video captioning and semantic search of overhead scenes, taking advantage of the photo-realism and ubiquitous access to high-level semantic information in a game like Grand Theft Auto. We train video captioning models and are surprised by how well their performance transfers to real drone, security camera, and even infrared footage in the face of poor video quality, compression artifacts, occlusion, and clutter. The speed of NVIDIA GPUs makes it possible to run the game engine with computationally heavy realism-augmenting mods, train video captioning models quickly, run captioning models faster than real-time video, and leverage commercially trained image models to quickly perform semantic search-by-example over large video datasets at scale.  Back
 
Topics:
Cyber Security, Intelligent Video Analytics, Computer Vision
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7237
Download:
Share:
 
Abstract:
We'll talk about the current performance limitations with VDI and its associated slow adoption; solutions to these limitations turning VDIs into the preferred medium for your environment; creating a better than PC experience with excellent m ...Read More
Abstract:

We'll talk about the current performance limitations with VDI and its associated slow adoption; solutions to these limitations turning VDIs into the preferred medium for your environment; creating a better than PC experience with excellent manageability; discovering the pitfalls of various system configurations and designs; and exploring the additional advantages of a VDI deployment for any environment.

  Back
 
Topics:
GPU Virtualization, Intelligent Video Analytics, Data Center & Cloud Infrastructure
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7109
Download:
Share:
 
Keynote (Keynote Talk)
Abstract:
Don't miss this keynote from NVIDIA Founder & CEO, Jensen Huang, as he speaks on the future of computing.
 
Topics:
Artificial Intelligence and Deep Learning, Data Center & Cloud Infrastructure, Virtual Reality & Augmented Reality, Autonomous Vehicles, Intelligent Video Analytics
Type:
Keynote
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7820
Streaming:
Share:
 
Abstract:
We'll describe the deep learning models behind Comcast's X1 Voice Remote and Smart Video Analytics and how we use GPUs to train and run these models. We'll explain how we can accurately parse the millions of voice queries we receive every day, how ...Read More
Abstract:
We'll describe the deep learning models behind Comcast's X1 Voice Remote and Smart Video Analytics and how we use GPUs to train and run these models. We'll explain how we can accurately parse the millions of voice queries we receive every day, how we automatically determine the domain of a query (TV, sports, billing, etc.), and how deep learning helps us understand what is happening on TV at any given moment. We'll also go into detail about how our distributed multi-GPU clusters speed up training the models and enable inference on millions of voice commands and hundreds of thousands video clips every day.  Back
 
Topics:
Artificial Intelligence and Deep Learning, Intelligent Video Analytics, Media and Entertainment
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7618
Download:
Share:
 
Abstract:
We'll highlight Sentinel, a system for real-time in-situ intelligent video analytics on mobile computing platforms. Sentinel combines state-of-the-art techniques in HPC with dynamic mode decomposition (DMD), a proven method for data reduction and an ...Read More
Abstract:
We'll highlight Sentinel, a system for real-time in-situ intelligent video analytics on mobile computing platforms. Sentinel combines state-of-the-art techniques in HPC with dynamic mode decomposition (DMD), a proven method for data reduction and analysis. By leveraging CUDA, our early system prototype achieves significantly better-than-real-time performance for DMD-based background/foreground separation on high-definition video streams, thereby establishing the efficacy of DMD as the foundation on which to build higher level real-time computer vision techniques. We'll present an overview of the Sentinel system, including the application of DMD to background/foreground separation in video streams, and outline our ongoing efforts to enhance and extend the prototype system.  Back
 
Topics:
Federal, Intelligent Video Analytics, In-Situ & Scientific Visualization, Artificial Intelligence and Deep Learning, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7685
Download:
Share:
 
Abstract:
We'll explain how to use Deep Features for enabling state-of-the-art results in visual object tracking. Visual object tracking is a difficult task in three respects, since (1) it needs to be performed in real-time, (2) the only available information ...Read More
Abstract:
We'll explain how to use Deep Features for enabling state-of-the-art results in visual object tracking. Visual object tracking is a difficult task in three respects, since (1) it needs to be performed in real-time, (2) the only available information about the object is an image region in the first frame, and (3) the internal object models needs to be updated in each frame. The use of Deep Features gives significant improvements regarding accuracy and robustness of the object tracker, but straightforward frame-wise updates of the object model become prohibitively slow for real-time performance. By introducing a compact representation of Deep Features, a smart updating mechanism, and exploiting systematically GPU implementations for feature extraction and optimization, real-time performance is achievable without jeopardizing tracking quality.  Back
 
Topics:
Computer Vision, Intelligent Video Analytics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7436
Download:
Share:
 
Abstract:
Arcvideo is top video solution provider in China, targeting broadcasting companies, TV stations, and recent booming game/entertainment live broadcasting and online education markets. Video codec, intelligent video analytics, universal end device play ...Read More
Abstract:
Arcvideo is top video solution provider in China, targeting broadcasting companies, TV stations, and recent booming game/entertainment live broadcasting and online education markets. Video codec, intelligent video analytics, universal end device player, and cloud video service are four pillars of our product line. We'll discuss GPU-accelerated intelligent video analytics, which plays an increasingly important role in video-related products and services, bringing more efficiency to handling tons of emerging video content, and better interaction between end users and their video interests.  Back
 
Topics:
Media and Entertainment, Intelligent Video Analytics, Video & Image Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7439
Download:
Share:
 
Abstract:
We'll present a novel framework to combine multiple layers and modalities of deep neural networks for video classification, which is fundamental to intelligent video analytics, including automatic categorizing, searching, indexing, segmentat ...Read More
Abstract:

We'll present a novel framework to combine multiple layers and modalities of deep neural networks for video classification, which is fundamental to intelligent video analytics, including automatic categorizing, searching, indexing, segmentation, and retrieval of videos. We'll first propose a multilayer strategy to simultaneously capture a variety of levels of abstraction and invariance in a network, where the convolutional and fully connected layers are effectively represented by the proposed feature aggregation methods. We'll further introduce a multimodal scheme that includes four highly complementary modalities to extract diverse static and dynamic cues at multiple temporal scales. In particular, for modeling the long-term temporal information, we propose a new structure, FC-RNN, to effectively transform the pre-trained fully connected layers into recurrent layers. A robust boosting model is then introduced to optimize the fusion of multiple layers and modalities in a unified way. In the extensive experiments, we achieve state-of-the-art results on benchmark datasets.

  Back
 
Topics:
Media and Entertainment, Autonomous Vehicles, Intelligent Video Analytics, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7497
Download:
Share:
 
 
Previous
  • Amazon Web Services
  • IBM
  • Cisco
  • Dell EMC
  • Hewlett Packard Enterprise
  • Inspur
  • Lenovo
  • SenseTime
  • Supermicro Computers
  • Synnex
  • Autodesk
  • HP
  • Linear Technology
  • MSI Computer Corp.
  • OPTIS
  • PNY
  • SK Hynix
  • vmware
  • Abaco Systems
  • Acceleware Ltd.
  • ASUSTeK COMPUTER INC
  • Cray Inc.
  • Exxact Corporation
  • Flanders - Belgium
  • Google Cloud
  • HTC VIVE
  • Liqid
  • MapD
  • Penguin Computing
  • SAP
  • Sugon
  • Twitter
Next