CamShift guided particle filter for visual tracking

被引：63

作者：

Wang, Zhaowen ^{[1
]}

Yang, Xiaokang ^{[1
]}

Xu, Yi ^{[1
]}

Yu, Songyu ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Image Commun & Informat Proc, Shanghai 200240, Peoples R China

来源：

PATTERN RECOGNITION LETTERS | 2009年 / 30卷 / 04期

关键词：

CamShift guided particle filter; Particle filter; CamShift; Visual tracking algorithm;

D O I：

10.1016/j.patrec.2008.10.017

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this article, a novel algorithm - CamShift guided particle filter (CAMSGPF) - is proposed for tracking object in video sequence. CamShift is incorporated into the probabilistic framework of particle filter as an optimization scheme for proposal distribution. Meanwhile, in the context of particle filter, the scale adaptation of CamShift is improved and the computation complexity is reduced. It is demonstrated through several real tracking tasks that the new method performs better than baseline trackers in both tracking robustness and computational efficiency. (c) 2008 Elsevier B.V. All rights reserved.

引用

页码：407 / 413

页数：7

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