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Research on gait recognition algorithm based on deep learning

The accuracy of gait recognition method would be affected by the occlusion of clothing object being carried. To overcome the problem, this paper adopted the method based on CNN(Convolutional neural network) and LSTM(Long and short term memory network) to build gait recognition models. Specifically, CNN is used to extract the spatial features of pedestrians in training videos, and the LSTM network is used to extract the temporal and spatial features of gait video sequences. We optimize the LSTM network structure and parameters of the gait recognition models and compare the establish models with the models built in other research. The results show that the models establish in our research perform better that the models in other research.