计算机工程与应用Issue(7)：169-173,5.DOI:10.3778/j.issn.1002-8331.1404-0418
基于列质量向量和SVM的步态识别
Gait recognition method based on column mass vector and support vector machine
摘要
Abstract
Gait recognition is based on the walk way to identity, with its unique advantages as a means of identification. In order to improve the gait recognition rate, this paper presents a novel approach for gait recognition based on column mass vector of body contour as feature, with support vector machine together effectively. According to the height and width of body contour to calculate gait cycle, it extractes column mass of body contour, finally, using support vector machine for classification. To verify the effectiveness, a lot of experiments have been performed in the CASIA gait database. Exper-imental verification of proposed method has higher recognition rate.关键词
列质量向量/宽高比/步态周期/支持向量机/步态识别Key words
column mass vector/aspect ratio/gait cycle/support vector machine/gait recognition分类
信息技术与安全科学引用本文复制引用
王开杰,杨天奇..基于列质量向量和SVM的步态识别[J].计算机工程与应用,2015,(7):169-173,5.基金项目
广州市科技计划项目（No.2014J4100107）。 （）
