No
Yes
View More
View Less
Working...
Close
OK
Cancel
Confirm
System Message
Delete
Schedule
An unknown error has occurred and your request could not be completed. Please contact support.
Scheduled
Wait Listed
Personal Calendar
Speaking
Conference Event
Meeting
Interest
Schedule TBD
Conflict Found
This session is already scheduled at another time. Would you like to...
Loading...
Please enter a maximum of {0} characters.
Please enter a maximum of {0} words.
must be 50 characters or less.
must be 40 characters or less.
Session Summary
We were unable to load the map image.
This has not yet been assigned to a map.
Search Catalog
Reply
Replies ()
Search
New Post
Microblog
Microblog Thread
Post Reply
Post
Your session timed out.
This web page is not optimized for viewing on a mobile device. Visit this site in a desktop browser to access the full set of features.
2017 GTC San Jose

S7289 - 3D Human Motion Capture from 2D Video Using Cloud-Based CNNs

Session Speakers
Session Description

This talk provides a brief overview of how to apply GPU-based deep learning techniques to extract 3D human motion capture from standard 2D RGB video. We describe in detail the stages of our CUDA-based pipeline from training to cloud-based deployment. Our training system is a novel mix of real world data collected with Kinect cameras and synthetic data based on rendering thousands of virtual humans generated in the Unity game engine. Our execution pipeline is a series of connected models including 2D video to 2D pose estimation and 2D pose to 3D pose estimation. We describe how this system can be integrated into a variety of mobile applications ranging from social media to sports training. A live demo using a mobile phone connected into an AWS GPU cluster will be presented.


Additional Session Information
Beginner
Talk
AI Startup Computer Vision and Machine Vision Deep Learning and AI Game Development Media and Entertainment
Media & Entertainment
25 minutes
Session Schedule