DocumentCode
3416557
Title
An approach based on particle swarm optimization for fast object detection
Author
Fan, Xinjian ; Li, Xiangdong ; Wang, Xuelin ; Xiao, Yongfei ; Zhi, Jianbin
Author_Institution
Shandong Provincial Key Lab. of Robot & Manuf. Autom. Technol. (SPKLRMAT), Inst. of Autom., Jinan, China
fYear
2011
fDate
19-21 Oct. 2011
Firstpage
120
Lastpage
124
Abstract
This paper describes a new object detection approach using particle swarm optimization (PSO). The approach is based on the idea that the task of finding a well-matched subwindow (object) can be formulated as an integer nonlinear optimization problem (INOP). We use PSO to solve this formulated INOP. Experiments in the domain of face detection are presented and the results show the effectiveness of the proposed method.
Keywords
face recognition; object detection; particle swarm optimisation; face detection; fast object detection; integer nonlinear optimization problem; particle swarm optimization; well matched subwindow; Face; Face detection; Object detection; Optimization; Particle swarm optimization; Search problems;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-61284-374-2
Type
conf
DOI
10.1109/IWACI.2011.6159986
Filename
6159986
Link To Document