An adaptive learning method for target tracking across multiple cameras

Kuan-Wen Chen*, Chih Chuan Lai, Yi Ping Hung, Chu Song Chen

*此作品的通信作者

研究成果: Conference contribution同行評審

70 引文 斯高帕斯(Scopus)

摘要

This paper proposes an adaptive learning method for tracking targets across multiple cameras with disjoint views. Two visual cues are usually employed for tracking targets across cameras: spatio-temporal cue and appearance cue. To learn the relationships among cameras, traditional methods used batch-learning procedures or hand-labeled correspondence, which can work well only within a short period of time. In this paper, we propose an unsupervised method which learns both spatio-temporal relationships and appearance relationships adaptively and can be applied to long-term monitoring. Our method performs target tracking across multiple cameras while also considering the environment changes, such as sudden lighting changes. Also, we improve the estimation of spatio-temporal relationships by using the prior knowledge of camera network topology.

原文English
主出版物標題26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
DOIs
出版狀態Published - 23 九月 2008
事件26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR - Anchorage, AK, United States
持續時間: 23 六月 200828 六月 2008

出版系列

名字26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Conference

Conference26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
國家/地區United States
城市Anchorage, AK
期間23/06/0828/06/08

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