In order to acquire accurate passenger flow information by locating and tracking moving pedestrians accurately in image sequence

a novel approach of head feature extraction based on target region matching is presented. Deferent from the common methods based on dense disparity image to obtain the disparity of the head region

the method in this paper is based on the idea of “segmentation before matching”

i.e. the reference image is segmented firstly by monocular image processing and the candidate head regions will be acquired. Then these candidate head regions will be taken as the target regions to be directly used in the correspondence regions searching and matching to obtain the head disparity. Finally the disparity of the candidate head regions is used to extract the depth and perspective feature of the candidate head regions to remove the false head regions. The performance test and experiment results show that the method proposed in this paper has the advantage of higher precision of disparity extraction and better real-time performance as well as the great importance to extract the pedestrian heads feature with high degree of distinction to effectively eliminate the false head regions so that the accuracy of the passenger flow detection can reach over 90%.