关键词: 多视角步态识别, 典型相关分析（CCA）, 局部判别CCA（LDCCA）, 加权LDCCA（WLDCCA）

Abstract: To solve the problem of gait feature extraction and overcome the influence of single observation angle on gait recognition rate, a Weighted Local Discriminent Canonical Correlation Analysis（WLDCCA） algorithm is proposed and then a multi-view gait recognition method is proposed. The main?characteristic?of?the proposed method is that the class information and local information is introduced into WLDCCA algorithm to effectively fuse the gait features of different views. The extracted fusion features can maximize the distance between intra-class samples and minimize the distance between inter-class samples at the same time, and then the recognition rate is greatly improved. The experimental results on the CASIA gait database verify the effectiveness and feasibility of the proposed algorithm.

Key words: multi-view gait recognition, Canonical Correlation Analysis（CCA）, Local Discriminnt CCA（LDCCA）, Weighted LDCCA（WLDCCA）