Probabilistic tracking with adaptive feature selection

被引：0

作者：

Chen, HT ^{[1
]}

Liu, TL ^{[1
]}

Fuh, CS ^{[1
]}

机构：

[1] Acad Sinica, Inst Informat Sci, Taipei 115, Taiwan

来源：

PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2 | 2004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 propose a color-based tracking framework that infers alternately an object's configuration and good color features via particle filtering. The tracker adaptively selects discriminative color features that well distinguish foregrounds from backgrounds. The effectiveness of a feature is weighted by the Kullback-Leibler observation model, which measures dissimilarities between the color histograms of foregrounds and backgrounds. Experimental results show that the probabilistic tracker with adaptive feature selection is resilient to lighting changes and background distractions.

引用

页码：736 / 739

页数：4