GTC ON-DEMAND

 
SEARCH SESSIONS
SEARCH SESSIONS

Search All
 
Refine Results:
 
Year(s)

SOCIAL MEDIA

EMAIL SUBSCRIPTION

 
 

GTC ON-DEMAND

Presentation
Media
Abstract:

Leaders from the mapping technology companies will discuss the advantages of various algorithms to create and maintain maps, followed by a short Q&A session. HERE: Vladimir Shestak, Lead Software Engineer Automated Driving Edge Perception for HD Map Maintenance: We start this talk by presenting a brief overview of HD Live Map created by HERE and its use for connected ADAS or automated driving solutions. Although building such a map with a required centimeter level precision is technically hard, the instant the HD Live Map is built, changes in the real world can occur causing the map to no longer reflect reality.  Hence, a proper maintenance strategy must be in place with the goal to identify discrepancies between the HD Live Map and the real world and heal the HD Live Map as quickly as possible. We discuss a spectrum of techniques developed by HERE to address the map-healing process and then focus on our low-cost solutions for in-vehicle change detection. The example system employs a consumer-grade Android-based sensing system streaming imagery and telemetry in real-time into HERE Edge Perception software stack. We present the high-level software architecture of the stack, its main components, i.e., feature detection, object tracking and triangulation, RWO and Maplet generation, as well as in-vehicle deployment options. The real-time performance evaluation of the system concludes our talk. NavInfo Europe:  Geetank Raipuria, Computer Vision Engineer Real-Time Object Detection and Semantic Segmentation: This session will discuss how NavInfo uses computer vision and deep learning to build high-definition maps that cover China's highways and large city streets. This involves performing object detection and semantic segmentation on visual imagery collected from vehicle sensors. The NavInfo Europe Advanced Research Lab creates processes that extract information from this data, both in real-time onboard vehicles using the NVIDIA DRIVE platform, and faster than real-time, processing offline gathered video material through NVIDIA DeepStream.

Leaders from the mapping technology companies will discuss the advantages of various algorithms to create and maintain maps, followed by a short Q&A session. HERE: Vladimir Shestak, Lead Software Engineer Automated Driving Edge Perception for HD Map Maintenance: We start this talk by presenting a brief overview of HD Live Map created by HERE and its use for connected ADAS or automated driving solutions. Although building such a map with a required centimeter level precision is technically hard, the instant the HD Live Map is built, changes in the real world can occur causing the map to no longer reflect reality.  Hence, a proper maintenance strategy must be in place with the goal to identify discrepancies between the HD Live Map and the real world and heal the HD Live Map as quickly as possible. We discuss a spectrum of techniques developed by HERE to address the map-healing process and then focus on our low-cost solutions for in-vehicle change detection. The example system employs a consumer-grade Android-based sensing system streaming imagery and telemetry in real-time into HERE Edge Perception software stack. We present the high-level software architecture of the stack, its main components, i.e., feature detection, object tracking and triangulation, RWO and Maplet generation, as well as in-vehicle deployment options. The real-time performance evaluation of the system concludes our talk. NavInfo Europe:  Geetank Raipuria, Computer Vision Engineer Real-Time Object Detection and Semantic Segmentation: This session will discuss how NavInfo uses computer vision and deep learning to build high-definition maps that cover China's highways and large city streets. This involves performing object detection and semantic segmentation on visual imagery collected from vehicle sensors. The NavInfo Europe Advanced Research Lab creates processes that extract information from this data, both in real-time onboard vehicles using the NVIDIA DRIVE platform, and faster than real-time, processing offline gathered video material through NVIDIA DeepStream.

  Back
 
Topics:
Autonomous Vehicles, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9351
Streaming:
Download:
Share:
 
Abstract:
Moderator: Dr. Justyna Zander, Global Head of Mapping, NVIDIA This session will discuss NVIDIA DRIVE Mapping, a platform that enables vehicle manufacturers to use maps from various global providers for highly accurate navigation and localization. DRIVE Mapping products integrate a scalable sensor suite, software development kits, and co-integrated high-definition maps from leading mapping companies. These end-to-end technologies help collect environmental data to create and update HD maps. We'll explain how the platform makes it possible for a self-driving vehicle to localize itself with precision, discern potential hazards, and determine exactly where it can safely drive. Leaders from the mapping technology companies will discuss the advantages of various modalities of maps and the benefit they provide to autonomous vehicles, followed by a short Q&A session. TomTom: Willem Strijbosch, Head of Autonomous Driving Mapping Progress on the Car-to-Cloud-to-Car Cycle The talk will discuss the latest on map creation and using crowdsourced data for map updates at TomTom.  3DMapping: Dr. Gunnar Gräfe, CEO and Founder Precise Ultra HD Map Data as Basis for Virtual Testing and Simulation Digital road data is the basis for virtual testing and simulation. Artificially designed digital roads may help case by case, but for various applications the precise digitalization and digital as-built representation of real-world roads is needed. The typical requirement is, that the roads used for virtual testing and simulation are regarded as digital twin of the real-world roads, which is prerequisite for comparable testing in reality and in the virtual environment. The technical solution for digitizing test tracks, race tracks and public roads with sufficient accuracy and resolution is high-end mobile surveying using high-resolution scanners and multiple cameras. 3D Mapping has invented the necessary technology since more than 20 years and today deploys van-based survey systems worldwide. The technology is used for example to generate high-resolution digital road surface models in OpenCRG format or to produce precise high definition reference maps in OpenDrive format, which are either used for virtual simulation and testing or as reference map in the car for autonomous driving development. 3D Mapping is member of the OpenDrive core team and has been intensively working on standardization and updates of the formats OpenDrive and OpenCRG since several years and is fully engaged in the ongoing ASAM format standardizations. The developments lead to new standards including 3D environment combined with scenario elements.
Moderator: Dr. Justyna Zander, Global Head of Mapping, NVIDIA This session will discuss NVIDIA DRIVE Mapping, a platform that enables vehicle manufacturers to use maps from various global providers for highly accurate navigation and localization. DRIVE Mapping products integrate a scalable sensor suite, software development kits, and co-integrated high-definition maps from leading mapping companies. These end-to-end technologies help collect environmental data to create and update HD maps. We'll explain how the platform makes it possible for a self-driving vehicle to localize itself with precision, discern potential hazards, and determine exactly where it can safely drive. Leaders from the mapping technology companies will discuss the advantages of various modalities of maps and the benefit they provide to autonomous vehicles, followed by a short Q&A session. TomTom: Willem Strijbosch, Head of Autonomous Driving Mapping Progress on the Car-to-Cloud-to-Car Cycle The talk will discuss the latest on map creation and using crowdsourced data for map updates at TomTom.  3DMapping: Dr. Gunnar Gräfe, CEO and Founder Precise Ultra HD Map Data as Basis for Virtual Testing and Simulation Digital road data is the basis for virtual testing and simulation. Artificially designed digital roads may help case by case, but for various applications the precise digitalization and digital as-built representation of real-world roads is needed. The typical requirement is, that the roads used for virtual testing and simulation are regarded as digital twin of the real-world roads, which is prerequisite for comparable testing in reality and in the virtual environment. The technical solution for digitizing test tracks, race tracks and public roads with sufficient accuracy and resolution is high-end mobile surveying using high-resolution scanners and multiple cameras. 3D Mapping has invented the necessary technology since more than 20 years and today deploys van-based survey systems worldwide. The technology is used for example to generate high-resolution digital road surface models in OpenCRG format or to produce precise high definition reference maps in OpenDrive format, which are either used for virtual simulation and testing or as reference map in the car for autonomous driving development. 3D Mapping is member of the OpenDrive core team and has been intensively working on standardization and updates of the formats OpenDrive and OpenCRG since several years and is fully engaged in the ongoing ASAM format standardizations. The developments lead to new standards including 3D environment combined with scenario elements.  Back
 
Topics:
Autonomous Vehicles
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9771
Streaming:
Download:
Share:
 
Abstract:
Autonomous driving requires thorough mapping capabilities in the car and in the cloud. In this session, various vendors present their mapping approaches to identify synergies and opportunities in the self-driving ecosystem.
Autonomous driving requires thorough mapping capabilities in the car and in the cloud. In this session, various vendors present their mapping approaches to identify synergies and opportunities in the self-driving ecosystem.  Back
 
Topics:
HD Mapping
Type:
Tutorial
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8861
Streaming:
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