1. TAIPEI | SEP. 21-22, 2016
Luke Liu, Sep 21 2016
EMBEDDED AND RELIABLE
COMPUTER VISION
2. 2
AGENDA
About LIPS
Turnkey Solution for Reliable Computer Vision
Implementation CV on Embedded System
Benefit from Depth Data for Machine Learning
Gesture and Posture Recognition base on CNN
Applications
Conclusion
3. 3
ABOUT LIPS
Focus on Human-Computer-Interface
Create a Real 3D World
Focus on Design Depth Camera
Focus on Parallel Computing
Focus on Machine Learning
Teach Computer to “Sense the World”
Sense the World
4. 4
TURNKEY SOLUTION FOR RELIABLE
COMPUTER VISION
LIPS (Solution Provider) = Hardware(Depth Camera) + Middleware (Software)
Application
OpenNI Framework
Depth optimization works
Driver for Android, Linux, Mac, and Windows OS
Application Development
5. 5
IMPLEMENTATION CV ON EMBEDDED SYSTEM
CUDA for Signal and Image Processing
Time-of-Flight Signal Processing
Image Processing for Reducing Noise
Real-Time Depth、IR and Image Data
Same Task on CPU and TK1 cost: 0.5 fps vs 60 fps
6. 6NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE.
BENEFIT FROM DEPTH DATA FOR MACHINE
LEARNING
Easy to segmentation from depth data
Clue: Depth data on a object is continuous
Normalization from depth data
Clue: Reduce same object for rotate
Goal: Object recognition with “Description”
Reduce Numerous Training Data
7. 7NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE.
GESTURE AND POSTURE RECOGNITION BASE
ON CNN
Video and Sponsorship for NVIDIA A.I. Robotics Competition 2016
8. 8NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE.
APPLICATIONS
3D Surveillance
Augmented Reality
Virtual Reality
Automotive
Drone
PDA with depth camera in logistic
9. 9NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE.
APPLICATIONS
TV/TV box NUI
Portable 3D scanner
Gaming
Digital Signage
Biometric recognition for access control system (Iris/face/gesture)
Robot vision
IoT
10. 10NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE.
CONCLUSION
GPU is suitable platform for Parallel and Image Processing
Depth data will reduce searching range and provide reliable computer vision
