关键词: 生物测量, 特征抽取, 步态识别, 主元分析法, 线性判决分析

Abstract: An appearance-based approach to the problem of gait recognition was adopted. The width of the outer contour of the binarized silhouette of a walking person was chosen as the basic image feature. A statistical method which combined Principal Component Analysis(PCA) with Linear Discriminant Analysis(LDA) for feature transformation of spatial templates was proposed. This method was used to reduce data dimensionality and to optimize the class separability of different gait sequences. Our method is applied to three data-sets(NLPR,CMU,UMF), extensive experimental results demonstrate that the proposed algorithm performs an encouraging recognition rate with relatively lower computational cost.

Key words: biometrics, feature extraction, gait-based recognition, PCA(Principal Component Analysis), LDA(Linear Discriminant Analysis)