A Fast and Robust People Counting Method in Video Surveillance
Enwei Zhang, Feng Chen · 2007
Video surveillance has become more and more prevalent. It is a basic problem to get the number of access people in scenes. When occlusions occur, it becomes difficult to count people. We propose a fast and robust people counting method, and implement a system. In our system, we use group tracking to compensate weakness of multiple human segmentation, which can handle complete occlusion. Our system can run in real-time about 30fps for CIF video, with counting accuracy defined by frame above 95%.