Gait Recognition Using Fuzzy Principal Component Analysis

Gait recognition is a relatively new biometric identification technology for human identification, surveillance and other applications. A novel gait recognition algorithm based on fuzzy principal component analysis (FPCA) for gait energy image(GEI) is proposed. Firstly, the original gait sequence is preprocessed and gait energy image is obtained. Secondly, the eigenvalues and eigenvectors are extracted by fuzzy principal component analysis, which are called fuzzy components. Then the eigenvectors are projected into lower-dimensional space. Finally, the NN classifier is utilized in feature classification. The method is tested on CASIA database. The experimental results show that this algorithm achieves higher recognition performance.