论文信息 - CLEAR'07 Evaluation of USC Human Tracking System for Surveillance Videos

CLEAR'07 Evaluation of USC Human Tracking System for Surveillance Videos

This paper presents the evaluation results of a system for tracking humans in surveillance videos. 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. Multi-threading techniques are used to speedup the process. Results are given on the video test set of the CLEAR-VACE surveillance human tracking evaluation task.

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