Data Science

Teaching Cameras to Read Body Language with AI

AI-Generated Summary

  • Wrnch, a Canadian startup backed by Mark Cuban and a member of the NVIDIA Inception program, demonstrated real-time deep learning software that reads body language from standard video at GTC 2018.
  • The AI engine runs on NVIDIA Tesla V100 GPUs and uses the TensorRT inference optimizer to track human motion with an off-the-shelf webcam.
  • The technology is currently applied in augmented reality, virtual reality, human-robot interaction, and motion capture applications.

Next Steps

  • Explore the GTC 2018 conference page for more event details.
  • Learn about the deep learning resources available from NVIDIA.
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At GTC 2018 in San Jose, California, AI developers from all over the world come to demo their work. One of those developers at the conference is a Canadian-based startup that developed a real-time deep learning software platform that can read body language from standard video.
Wrnch, a Mark Cuban-backed startup, and a member of the NVIDIA Inception program, was founded by Dr. Paul Kruszewski in 2015. The team uses NVIDIA Tesla V100 GPUs and the TensorRT inference optimizer for its AI engine.
At GTC, using an off-the-shelf Logitech webcam, the team has set-up a demo that can track and capture human motion without the use of special cameras, bodysuits or sensors.


Dr. Kruszweski explained that his AI system can potentially be used to recognize accidents at home or in the workplace, helping autonomous vehicles read human intent, and even improving interactions between humans and robots.
The startup’s deep learning software is currently in use in AR, VR, human-robot interaction, and motion capture applications.
“Every camera on the planet can be taught to read human body language to make life safer, healthier and more fun,” Kruszweski said.
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