An optimized hierarchical classifier for pedestrian detection
Xu, Yanwu; Cao, Xianbin; Qiao, Hong
2008
Conference Name7th World Congress on Intelligent Control and Automation
Source Publication2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION
Conference DateJUN 25-27, 2008
Conference PlaceChongqing, PEOPLES R CHINA
AbstractClassification is an essential technology in Pedestrian Detection System (PDS). Until now, single-classifier and basic cascaded classifier had been widely used in PDS; however, most of them can hardly satisfy the 3 requirements at the same time: high detection speed, high detection rate and low false positive rate. In this paper, we proposed an optimized hierarchical classifier which can satisfy the 3 requirements. The proposed method adopted Corse-to-fine and Early-rejection principles to achieve global high performance. It consists of two hierarchies, the first one is used to quickly reject non-pedestrian objects and select out only a few candidates; the second one makes further verification to these candidates. Furthermore, each hierarchy was optimized with statistical models basing on experiments; and each hierarchy is a treelike classifier which has specific optimization demands. At last; an overall performance evaluation standard is proposed, and the experimental results showed that the proposed classifier had better overall performance.
KeywordPedestrian Detection Hierarchical Classifier Adaboost
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12814
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Corresponding AuthorXu, Yanwu
AffiliationUniv Sci & Technol China, Dept Comp Sci & Technol
Recommended Citation
GB/T 7714
Xu, Yanwu,Cao, Xianbin,Qiao, Hong. An optimized hierarchical classifier for pedestrian detection[C],2008.
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