Particle swarm optimization for object detection and segmentation

被引：0
|
作者：
Cagnoni, Stefano [1 ]
Mordonini, Monica [1 ]
Sartori, Jonathan [1 ]
机构：
[1] Univ Parma, Dipartimento Ingn Informazione, Viale G Usberti 181 A, I-43100 Parma, Italy
来源：
APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS | 2007年 / 4448卷
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：
In this paper we describe results of a modified Particle Swarm Optimization (PSO) algorithm which has been applied to two image analysis tasks. in the former, accurate region-based segmentation is obtained by analyzing the cumulative results of several runs of the algorithm. In the latter, the fast-convergence properties of the algorithm are used to accurately locate and track an object of interest in real time.
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页码：241 / +
页数：2
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