Evaluation of USC Human Tracking System for Surveillance Videos

The evaluation results of a system for tracking humans in surveillance videos are presented. Moving blobs are detected based on adaptive background modeling. A shape based multi-view human detection system is used to find humans in moving regions. The detected responses are associated to infer the human trajectories. The shaped based human detection and tracking is further enhanced by a blob tracker to boost the performance on persons at a long distance from the camera. Finally the 2D trajectories are projected onto the 3D ground plane and their 3D speeds are used to verified the hypotheses. Results are given on the video test set of the VACE surveillance human tracking evaluation task.