计算机应用研究2012，Vol.29Issue(1)：355-358,4.DOI:10.3969/j.issn.1001-3695.2012.01.098
基于线性插值的张量步态识别算法
Tensor gait recognition algorithm based on linear interpolation
摘要
Abstract
This paper proposed a novel tensor gait recognition algorithm based on linear interpolation. To make the tested gait sequence match with register ones, the sizes of these two should surely be consistent. First and foremost, the number of frames in one gait cycle should be normalized to a certain amount by linear interpolation of both nearest neighbor frames j gnd then one gait sample could be represented as a tensor. After that, employed MPCA here for tensor analysis. It was determined that a whole period composed to a single gait sample was more efficient than a half period in the experiments carried out on CASIA (B) gait database. This proposed method has achieved an encouraging recognition result.关键词
步态识别/线性插值/张量表达/多重线性主成分分析Key words
gait recognition/ linear interpolation/ tensor representation/ multilinear principal component analysis (MPCA)分类
信息技术与安全科学引用本文复制引用
贲晛烨,安实,王健,王科俊..基于线性插值的张量步态识别算法[J].计算机应用研究,2012,29(1):355-358,4.基金项目
中国博士后科学基金面上资助项目(20110491087) （20110491087）
