标题:Gait Recognition Using Procrustes Shape Analysis and Shape Context
作者:Zhang, Yuanyuan; Yang, Niqing; Li, Wei; Wu, Xiaojuan; Ruan, Qiuqi
通讯作者:Wu, X
作者机构:[Zhang, Yuanyuan; Yang, Niqing; Li, Wei; Wu, Xiaojuan] Shandong Univ, Sch Informat Sci & Engn, 27 Shanda Nanlu, Jinan 250100, Peoples R China.; [Rua 更多
会议名称:9th Asian Conference on Computer Vision
会议日期:SEP 23-27, 2009
来源:COMPUTER VISION - ACCV 2009, PT III
出版年:2010
卷:5996
期:PART 3
页码:256-265
DOI:10.1007/978-3-642-12297-2_25
关键词:Gait recognition; Procrustes shape analysis; shape context descriptor;; Procrustes Mean Shape (PMS)
摘要:This paper proposes a. novel algorithm for individual recognition by gait. The method of Procrustes shape analysis is used to produce Procrustes Mean Shape (PMS) as a compressed representation of gait sequence. PIMS is adopted as the gait signature in this paper. Instead of using the Procrustes mean shape distance as a similarity measure, we introduce shape context descriptor to measure the similarity between two PMSs. Shape context describes a distribution of all boundary points on a shape with respect to any single boundary point by a histogram of log-polar plot, and offers us a global discriminative characterization of the shape. Standard pattern recognition techniques are used to classify different patterns. The experiments on CASIA Gait Database demonstrate that the proposed method outperforms other algorithms in both classification performance and verification performance.
收录类别:CPCI-S;EI;SCOPUS
WOS核心被引频次:2
Scopus被引频次:7
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650479085&doi=10.1007%2f978-3-642-12297-2_25&partnerID=40&md5=34df7237ed871095cec20615985e141b
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