Real-time human body parts localization from dynamic vision sensor

Dynamic vision sensor (DVS) as a novel type of visual sensors can detect a moving object in a fast and cost effective way by outputting events on edges of the object. This paper proposes a body part localization method using structured output Deep Belief Network (s-DBN) to label the body parts in block of pixels in very fast fashion. Experiments show that our proposed algorithm achieves pixel accuracy 90.13% on body parts localization compared to Deep Belief Network (87.01%) and Random Forests (84.15%) under the same computational cost. For head/hand detection s-DBN has significant better accuracy of 99.3%/87.8% compared to DBN 98.7%/81.7% and RF 97.1%/47.1% under recall rate 99%/90%. Specifically, the process time on a 240×180 sized image is less than 1ms on Intel Core2 2.83GHZ CPU.