TAIPEI | SEP. 21-22, 2016

Luke Liu, Sep 21 2016

EMBEDDED AND RELIABLE COMPUTER VISION

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

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

TURNKEY SOLUTION FOR RELIABLE COMPUTER VISION

LIPS (Solution Provider) = Hardware(Depth Camera) + Middleware (Software)

Application

OpenNI Framework

Depth optimization worksDriver for Android, Linux, Mac, and Windows OS

Application Development

5

IMPLEMENTATION CV ON EMBEDDED SYSTEMCUDA 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

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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

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GESTURE AND POSTURE RECOGNITION BASE ON CNN

Video and Sponsorship for NVIDIA A.I. Robotics Competition 2016

8NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE.

APPLICATIONS

3D Surveillance

Augmented Reality

Virtual Reality

Automotive

Drone

PDA with depth camera in logistic

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APPLICATIONS

TV/TV box NUI

Portable 3D scanner

Gaming

Digital Signage

Biometric recognition for access control system (Iris/face/gesture)

Robot vision

IoT

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CONCLUSION

GPU is suitable platform for Parallel and Image Processing

Depth data will reduce searching range and provide reliable computer vision

TAIPEI | SEP. 21-22, 2016

THANK YOU