改进的完全二维主成分分析及其在步态识别中的应用研究

摘要

This paper improved complete two dimensional principal component analysis, and proposed three different weighted strategies.It analyzed the essence of weighted scheme in detail.To evaluate the validity of the proposed method and apply it to gait recognition, it conducted experiments on CASIA (B) gait database.Experimental results show that the selection of weighted power exponent has great influence on the recognition result, and can improve the recognition performance by picking the best weight value in experiments.In the end, discussed the reason why the recognition rate of gait with a bag was low in the various walking states.%对完全二维主成分分析算法进行改进,提出三种不同的加权策略,详细地分析它们的本质,并将其应用到步态识别中.在中国科学院自动化所提供的CASIA(B)步态数据库下验证加权方案的有效性,实验结果表明加权幂指数的选取对识别结果的影响比较大,通过实验可以选取最佳的权值,能够做到提高识别性能.最后针对各个行走状态下的步态,分析了背包步态识别率低的原因.