An optimal fuzzy system for feature reliability measuring in particle filter-based object tracking

被引：0
|
作者：
Komeili, M. [1 ]
Valizadeh, M. [1 ]
Armanfard, N. [1 ]
Kabir, E. [1 ]
机构：
[1] Tarbiat Modares Univ, Dept Elect Engn, Tehran, Iran
来源：
2009 14TH INTERNATIONAL COMPUTER CONFERENCE | 2009年
关键词：
D O I：
10.1109/CSICC.2009.5349435
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, a fuzzy inference system by which reliability of features can be measured is designed. The reliability determines discriminative power of a feature in separating target from background. We focus our attention on design of membership functions. With a rational explanation on available information over a particle filter-base tracking process, we infer a coarse estimation of membership functions. It follows with a fine-tuning stage by using genetic algorithm. Color, edge, texture and TED are used in current work but the extension to a wider number of features is straightforward.
引用
收藏
页码：47 / 53
页数：7
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