Tracking algorithm using background-foreground motion models and multiple cues

被引：0
|
作者：
Shao, J [1 ]
Zhou, SK [1 ]
Chellappa, R [1 ]
机构：
[1] Univ Maryland, Ctr Automat Res, College Pk, MD 20742 USA
来源：
2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING | 2005年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a stochastic tracking algorithm for surveillance videos where targets are dim and of low resolution. Our tracker is mainly based on the particle filter algorithm. Two important novel features of the tracker include: A motion model consisting of both background and foreground motion parameters is built. Multiple cues are adaptively integrated in a system observation model when estimating the likelihood functions. Based on these features, the accuracy and robustness of the tracker has been improved, which is very important for surveillance problems. We present the results of applying the proposed algorithm to many videos.
引用
收藏
页码：233 / 236
页数：4
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