Real-time system for human detection and tracking at different distances

A real-time robust human detection and tracking system is proposed, which can detect people in the monitoring area and then keep tracking. To reduce the working range, a background subtraction technique is used to segment the moving foreground and the background. Since each body feature has its optimum working distance, several different detectors such as frontal face, head, and pedestrian are combined. By taking the video sequence continuity and the human body geometry constraint into account, robust real-time detection is achieved. The proposed system reduces the occurrence of tracking failure and enhances performance even with dramatic distance change between camera and people.