arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1502.03532cs.CV

An equalised global graphical model-based approach for multi-camera object tracking

Institute of Automation, Chinese Academy of Sciences(中国科学院自动化研究所);National Laboratory of Pattern Recognition(模式识别国家重点实验室)

Weihua Chen, Lijun Cao, Xiaotang Chen, Kaiqi Huang

英文摘要:

Non-overlapping multi-camera visual object tracking typically consists of two steps: single camera object tracking and inter-camera object tracking. Most of tracking methods focus on single camera object tracking, which happens in the same scene, while for real surveillance scenes, inter-camera object tracking is needed and single camera tracking methods can not work effectively. In this paper, we try to improve the overall multi-camera object tracking performance by a global graph model with an improved similarity metric. Our method treats the similarities of single camera tracking and inter-camera tracking differently and obtains the optimization in a global graph model. The results show that our method can work better even in the condition of poor single camera object tracking.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑