The treelike assembly classifier for pedestrian detection
Wei, C. X.; Cao, X. B.; Xu, Y. W.; Qiao, Hong; Wang, Fei-Yue
Conference NamePacific Asia Workshop on Intelligence and Security Informatics
Conference DateAPR 11-12, 2007
Conference PlaceChengdu, PEOPLES R CHINA
AbstractUntil now, classification is a primary technology in Pedestrian Detection. However, most existing single-classifiers and cascaded classifiers can hardly satisfy practical needs (e.g. false negative rate, false positive rate and detection speed). In this paper, we proposed an assembly classifier which was specifically designed for pedestrian detection in order to get higher detection rate and lower false positive rate at high speed. The assembly classifier is trained to select out the best single-classifiers, all of which will be arranged in a proper structure; finally, a treelike classifier is obtained. The experimental results have validated that the proposed assembly classifier generates better results than most of the existing single-classifiers and cascaded classifiers.
Document Type会议论文
Corresponding AuthorWei, C. X.
AffiliationUniv Sci & Technol China, Dept Comp Sci & Technol
Recommended Citation
GB/T 7714
Wei, C. X.,Cao, X. B.,Xu, Y. W.,et al. The treelike assembly classifier for pedestrian detection[C],2007.
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