An approach based on particle swarm optimization for fast object detection

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....

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Bibliographic Details
Main Authors: Xinjian Fan, Xiangdong Li, Xuelin Wang, Yongfei Xiao, Jianbin Zhi
Format: Conference Proceeding
Language:English
Subjects:
Face
Face detection
Object detection
Optimization
Particle swarm optimization
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Summary: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.
DOI:10.1109/IWACI.2011.6159986