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GTC ON-DEMAND

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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.

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.

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Topics:
Intelligent Video Analytics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8945
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