| Citation: | ZHANG Zihao, WANG Rong. Improved face recognition method based on MobileFaceNet network[J]. Journal of Beijing University of Aeronautics and Astronautics, 2020, 46(9): 1756-1762. doi: 10.13700/j.bh.1001-5965.2020.0049(in Chinese)
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In order to solve the problem of more convolutional model parameters and slower convergence speed during training, an improved face recognition method based on MobileFaceNet network is proposed. First, we use the MobileFaceNet network to extract facial features. In the process of extracting features, the number of convolutional layer parameters in the model is reduced by introducing separable convolution. Then, the style attention mechanism is introduced in the MobileFaceNet network to enhance the expression of features. At the same time, the AdaCos face loss function is used to train the model, and the adaptive scaling factor in the AdaCos loss function is used to dynamically adjust the hyperparameters to avoid the effect of artificially setting hyperparameters on the model. Finally, we evaluate the training model on the LFW, AgeDB and CFP-FF test dataset, respectively. The experimental results show that the recognition accuracy of the improved model on the LFW, AgeDB and CFP-FF test dataset has increased by 0.25%, 0.16% and 0.3%, respectively, indicating that the improved model has higher accuracy and robustness than the model before improvement.
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