Co-evolution based feature selection for pedestrian detection
Guo, Y.P.; Cao, X.B.; Xu, Y.W.; Hong, Q.
2007
会议名称2007 IEEE International Conference on Control and Automation, ICCA 2007
会议录名称2007 IEEE International Conference on Control and Automation, ICCA 2007
会议日期30 May-1 June 2007
会议地点Guangzhou, China
摘要In a pedestrian detection system, the most critical requirement is to quickly and reliably determine whether a candidate region contains a pedestrian. The detection ability of whole system determines directly upon quality of chosen features. However, due to the large number and various types of available features, it is difficult to find an optimal feature subset and acquire the proper feature proportion at the same time for most traditional methods including AdaBoost Algorithm. This paper presents a co-evolutionary method with sub-population size adjusting strategy for the feature selection problem in pedestrian detection system. Our method is able to find an optimal feature subset and adjust feature proportion to a proper state in the mean time. Experiments show that our method performs better than AdaBoost Algorithm.
关键词Automated Highways / Object Detection / Road Safety / Adaboost Algorithm / Coevolution Based Feature Selection / Pedestrian Detection System / Automatic Control / Automation / Communication System Software / Computer Science
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12823
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
通讯作者Guo, Y.P.
作者单位Dept. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China
推荐引用方式
GB/T 7714
Guo, Y.P.,Cao, X.B.,Xu, Y.W.,et al. Co-evolution based feature selection for pedestrian detection[C],2007.
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