Face Recognition Based on MTCNN and Convolutional Neural Network | Zendy

Hongchang Ku | Zendy; Dong Wei | Zendy

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Face Recognition Based on MTCNN and Convolutional Neural Network

Author(s) -

Hongchang Ku,

Dong Wei

Publication year - 2019

Publication title -

frontiers in signal processing

Language(s) - English

Resource type - Journals

eISSN - 2521-7380

pISSN - 2521-7372

DOI - 10.22606/fsp.2020.41006

Subject(s) - convolutional neural network , computer science , artificial intelligence , convolution (computer science) , face (sociological concept) , pattern recognition (psychology) , face detection , facial recognition system , artificial neural network , deep learning , computer vision , social science , sociology

MTCNN is a face detection method based on deep learning, which is more robust to light, angle and facial expression changes in natural environment, and has better face detection effect. At the same time, the memory consumption is small, and real-time face detection can be realized. Therefore, a method based on MTCNN and improved convolution neural network is proposed in this paper. Firstly, MTCNN is used to detect and align faces. Then, the output image is used as the input data of the improved convolution network, and multi-level convolution training is carried out. Finally, the accuracy of the model is tested.

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