Rao-Blackwellised particle filter for colour-based tracking

被引:16
|
作者
Martinez-del-Rincon, Jesus [1 ]
Orrite, Carlos [1 ]
Medrano, Carlos [1 ]
机构
[1] Univ Zaragoza, Comp Vis Lab, Aragon Inst Engn Res, Zaragoza 50001, Spain
关键词
Rao-Blackwellised particle filter; Colour updating; Tracking; PDA Kalman filter; Kernel density estimation;
D O I
10.1016/j.patrec.2010.08.006
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Colour-based particle filters have been used exhaustively in the literature given rise to multiple applications However tracking coloured objects through time has an important drawback since the way in which the camera perceives the colour of the object can change Simple updates are often used to address this problem which imply a risk of distorting the model and losing the target In this paper a joint image characteristic-space tracking is proposed which updates the model simultaneously to the object location In order to avoid the curse of dimensionality a Rao-Blackwellised particle filter has been used Using this technique the hypotheses are evaluated depending on the difference between the model and the current target appearance during the updating stage Convincing results have been obtained in sequences under both sudden and gradual illumination condition changes Crown Copyright (C) 2010 Published by Elsevier B V All rights reserved
引用
收藏
页码:210 / 220
页数:11
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