Vision-based pedestrian tracking system using color and motion cue

Meiqing Wu, Siew Kei Lam, Thambipillai Srikanthan, Tushar Shah

Abstract: Pedestrian tracking is becoming increasingly important for intelligent vehicles to improve the safety on road. Vision based pedestrian tracking with moving cameras faces notorious challenges. The classical background subtraction technique in surveillance applications is no longer applicable for Advanced Driver Assistance Systems (ADASs). In this paper, we propose a vision based pedestrian tracking algorithm which relies on color and motion information. First, pedestrians are detected using the HOG human detector in each image frame. The detected pedestrians are then associated over video frames based on fusion of color-based similarity and motion-based similarity between two image regions. Our studies reveal that the utilization of histogram in the proposed method contributes to high computational complexity. As such, preliminary results for a hardware-efficient implementation of histogram generation and comparison technique have been presented.