关键词: 步态识别, 核二维主成分分析, 支持向量机

Abstract: Gait recognition is a new biometric identification technology, it is the identity of the methods to identify people by the way they walk. In this paper, in order to carry on extraction and recognition of human gait characteristics more rapidly and effectively, a method is used based on the Kernel two Dimensional Principal Component Analyses（K2DPCA） to get the gait feature extraction and Support Vector Machine（SVM） method to identify. The algorithm obtains the gait quasi-periodicity through analyzing the width information of the lower limbs’ gait contour edge, and the GEI is calculated from gait period. The kernel two dimensional principal component analysis method is used to extract gait feature vector generated by the GEI, the SVM classifier is adopted to distinguish the differences. Experimental results show that the method proposed in this paper is efficient.

Key words: gait recognition, kernel two dimensional principal component analyses, support vector machine