GESTURE RECOGNITION: USING A MULTI SENSOR APPROACH SHALINI GUPTA, PAVLO MOLCHANOV, KIHWAN KIM, KARI PULLI, JAN KAUTZ NVIDIA RESEARCH
DRIVER DISTRACTION
GESTURE INTERFACE (http://www.softkinetic.com)
DAY
DAY NIGHT
NO SUNLIGHT
NO SUNLIGHT SUNLIGHT
MULTI-SENSOR SOLUTION COLOR + DEPTH RADAR sensors
MULTI-SENSOR SOLUTION COLOR + DEPTH RADAR gesture UI sensors
3.2% INCREASED ACCURACY +1.5m/s 0 m/s -1.5m/s 3D shape color velocity
16X POWER EFFICIENCY velocity power v 0.15W t
16X POWER EFFICIENCY velocity power v 2.5 W v T 0.15W gesture gesture t
SHORT RANGE FMCW RADAR radar prototype
SHORT RANGE FMCW RADAR y +1.5m/s 0 m/s x v radar prototype 4D vector z -1.5m/s
POSITION RESULTS
VELOCITY RESULTS +1.5m/s 0 m/s -1.5m/s
GESTURE NETWORK fully connected NN logistic regression 60 3D convolutional frames layer subsampling layer Trained on GPU
10 GESTURES PALM up down left right SHAKE SWIPE right left ROTATION CALL clockwise counter-clockwise
INDOOR CAR SIMULATOR
OUTDOOR CAR
ERROR RATE 39.90% 10.90% 9.10% C D R D+C R+D R+C R+D+C D – depth C – color R - radar
ERROR RATE 39.90% 10.90% 9.10% 7.90% 8.30% 7.40% C D R D+C R+D R+C R+D+C D – depth C – color R - radar
ERROR RATE 39.90% 10.90% 9.10% 7.90% 8.30% 7.40% 5.90% C D R D+C R+D R+C R+D+C D – depth C – color R - radar
ERROR RATE 20.90% D+R (CNN) D+R+C (CNN) 9.70% 6.70% D+C (HOG) 3.00% Night Evening Day (shadow) Day (sunlight) D – depth C – color R - radar
ERROR RATE 20.90% D+R (CNN) D+R+C (CNN) 9.70% 6.70% 6.70% D+C (HOG) 8.30% 7.50% 3.00% 1.50% Night Evening Day (shadow) Day (sunlight) D – depth C – color R - radar
ERROR RATE 22.20% 20.90% D+R (CNN) 13.00% D+R+C (CNN) 6.70% D+C (HOG*) 8.30% 7.50% 2.45% 1.50% Night Evening Day (shadow) Day (sunlight) D – depth C – color * Ohn-Bar and Trivedi, IEEE Trans. on R - radar Intelligent Transportation Systems , 2014.
DEMO 52ms on Quadro 6000
CONCLUSION COLOR + DEPTH RADAR 1 GESTURE UI 2 1 Multi- sensor System for Driver’s Hand -Gesture Recognition , IEEE Automatic Face and Gesture Recognition, May 2015. 2 Short-Range FMCW Monopulse Radar for Hand-Gesture Sensing , IEEE International Radar Conference, May 2015.
THANK YOU SHALINIG@NVIDIA.COM
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