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. 1 Task and Data Set The task in this evaluation exercise is to track the 2D locations and regions of multiple humans in surveillance videos. The videos are captured with a single static camera mounted a few meters above the ground looking down towards a street. The test set for the evaluation contains 50 sequences of 150 seconds each, captured from two ...

• Type: Conference
• Year: 2007
• Where: CLEAR
• Authors: Bo Wu, Vivek Kumar Singh, C.-H. Kuo, Li Zhang, Sung Chun Lee, Ramakant Nevatia
• Keywords: Biometrics, CLEAR 2007, Human Detection, Multi-view Human Detection, Surveillance Videos