Gait feature extraction based on restricted Boltzmann machine and its recognition method

doi:10.3969/j.issn.1000-1565.2019.06.014

Abstract

Abstract: Aiming at gait recognition, the gait feature extraction and recognition of restricted Boltzmann machine(RBM)are studied. Based on the human pedestrian image sequence, the gait energy map is generated by background segmentation, normalization and gait cycle calculation. The gait energy map is used as the feature image of gait, and the gait feature is automatically acquired by RBM. The gait database of Chinese Academy of Sciences CASIA is chosen to study the gait recognition using RBM method for different classification methods, including support vector machine, twin support vector machine, neural network and K-nearest neighbor method. At the same time, this approach is compared with PCA, LDA and CNN feature extraction and recognition.

Key words: restricted Boltzmann machine(RBM), gait energy map, feature extraction, gait recognition

CLC Number:

TP391

LI Kai, CAO Kefan. Gait feature extraction based on restricted Boltzmann machine and its recognition method[J]. Journal of Hebei University (Natural Science Edition), 2019, 39(6): 657-665.

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