Real-Time Pedestrian Detection and Tracking

This paper presents an embedded prototype system for pedestrian detection and tracking in outdoor scenes. The system uniquely combines two common techniques for motion detection-temporal differencing and background subtraction. The results of these two techniques are adaptively averaged and thresholded to result in a binary motion image. Motion regions are efficiently segmented and non-target regions are removed. Detected pedestrians are tracked based on their location in previous frames. Both motion detection and tracking were designed with an embedded environment in mind and were optimized for the C6000 family of DSPs. A fixed-point version of the human detection and tracking algorithm was implemented using the DM642 EVM board. The proposed system and algorithm were verified to be accurate and robust by a set of experiments at real scenarios. A real-time implementation for D1 resolution shows the efficiency of the algorithm and proves the suitability of the DM642 chip for such a system. 1