Abstract: A gait recognition algorithm is proposed based on fuzzy theory classification
decision double-directional two-dimensional principal component analysis (DTPCA) for the
problems of high dimensionality and difficult classification of mean gait energy image (MGEI)
coefficient matrix. A preprocess technique is used to obtain MGEI, which is then divided into
some of sub-image blocks, then DTPCA is used to reduce the dimension of mean gait energy
sub-image blocks coefficient matrix and improve the recognition speed. The fuzzy theory is
introduced to classify the nearest-neighbour classifiers. The proposed algorithm is evaluated on
CASIA Gait Database. Experimental results show that the proposed approach achieves a high
recognition accuracy and stronger robustness.

Key words: gait recognition, mean gait energy image (MGEI), principal component analysis
(PCA), double-directional two-dimensional principal component analysis (DTPCA)