People Counting Based on Top-View Video Sequence

[[abstract]]In this paper, a people counting system based on top-view video sequences is proposed. This system consists of foreground people detection and people counting algorithm. For people detection, an image segmentation method based on k-means clustering is employed to extract human figures. In order to use in different of illumination conditions, we use region merging to remove shadows of each object. With this approach, our system can be applied in outdoor environments. In the people counting part, human regions are tracked and counted based on a graph matching algorithm. Tracking results are used to determine the direction of region movement based on unary and binary features. Our system has been tested in many different cases of pedestrian density. We give examples of the system counting people in real-time in describe.