BINOCULAR PEDESTRIAN DETECTION SYSTEM HAVING DUAL-STREAM DEEP LEARNING NEURAL NETWORK AND THE METHODS OF USING THE SAME

摘要

Aspects of present disclosure relates to a binocular pedestrian detection system (BPDS). BPDS includes: a binocular camera to capture certain binocular images of pedestrians passing through a predetermined area, an image/video processing ASIC to process binocular images captured, and a binocular pedestrian detection system controller having a processor, a network interface, and a memory storing computer executable instructions. When executed by processor, computer executable instructions cause processor to perform: capturing, by binocular camera, binocular images of pedestrians, binocularly rectifying binocular images, calculating disparity maps of binocular images rectified, training a dual-stream deep learning neural network, and detecting pedestrians passing through predetermined area using dual-stream deep learning neural network trained. Dual-stream deep learning neural network includes a neural network for extracting disparity features from disparity maps of binocular images, and a neural network for learning and fusing features from rectified left images and disparity maps of binocular images.