A camera-based system for tracking people in real time

This paper describes a system for real-time tracking of people in video sequences. The input to the system is live or recorded video data acquired by a stationary camera in an environment where the primary moving objects are people. The output consists of trajectories which give the spatio-temporal coordinates of individual persons as they move in the environment. The system uses a new model-based approach to object tracking. It identifies feature points in each video frame, matches feature points across frames to produce feature “paths”, then groups short-lived and partially overlapping feature paths into longer living trajectories representing motion of individual persons. The path grouping is based on a novel model-based algorithm for motion clustering. The system runs on an SGI Indy workstation at an average rate of 14 frames a second. The system has numerous applications since various statistics and indicators of human activity can be derived from the motion trajectories. Examples of these indicators described in the paper include people counts, presence and time spent in a region, traffic density maps and directional traffic statistics