A color-based particle filter for joint detection and tracking of multiple objects

被引：0
|
作者：
Czyz, J [1 ]
Ristic, B [1 ]
Macq, B [1 ]
机构：
[1] Catholic Univ Louvain, TELE, B-1348 Louvain, Belgium
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：
Recent works have shown that the particle filter using color as observation feature is a powerful technique for tracking deformable objects in image sequences with complex backgrounds. This paper presents a hybrid valued sequential state estimation algorithm, and its particle filter-based solution, that extends the standard color particle filter in two ways. Firstly, track initialization is embedded in the particle filter without relying on an external target detection algorithm. Secondly, the algorithm is able to track multiple objects sharing the same color description. We evaluate the performance of the proposed filter on various real-world video sequences with appearing and disappearing targets.
引用
收藏
页码：217 / 220
页数：4
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