哈尔滨工程大学学报2009，Vol.30Issue(9)：1022-1028,7.DOI:10.3969/j.issn.1006-7043.2009.09.010
基于广义主成分分析的步态识别算法研究
Research on a gait recognition algorithm based on generalized principal component analysis
摘要
Abstract
Gait recognition makes use of human walking patterns for biometric recognition and is a novel topic in the field. Effective segmentation using a simple method to extract silhouettes of walking figures from the background was the first step of our method; this played a key role in gait recognition. Then, morphology was used and a standardized and centralized image was obtained by geometric transformation. Afterwards gait energy image (GEI) was used as a feature extraction method--describing gait characteristics obtained using periodic sequence images according to their cyclical divisions. Following this, feature dimensionality was reduced through principal component analysis (PCA), two-dimensional principal component analysis (2DPCA), complete two-dimensional principal component analysis (C2DPCA) and weighted complete two-dimensional principal component analysis (WC2DPCA) respectively. The nearest neighbor classifier was then used to distinguish different human gaits. By balancing calculation and recognition rates, experimental results demonstrated that 2DPCA based on GEI has encouraging recognition performance with a recognition rate of about 95.43%.关键词
步态识别/步态能量图/主成分分析/二维主成分分析/加权完全的二维主成分分析Key words
gait recognition/ GEI (gait energy image) / PCA (principal component analysis) / 2DPCA (two-dimensional principal component analysis) / WC2DPCA (weighted complete two-dimensional principal component analysis)分类
信息技术与安全科学引用本文复制引用
王科俊,贲晛烨,孟玮,魏娟..基于广义主成分分析的步态识别算法研究[J].哈尔滨工程大学学报,2009,30(9):1022-1028,7.基金项目
国家"863"计划资助项目(2008AA01Z148) （2008AA01Z148）
黑龙江省杰出青年科学基金资助项目(JC200703) （JC200703）
哈尔滨市科技创新人才研究专项基金资助项目(2007RFXXG009). （2007RFXXG009）
