Research on face detection method based on improved MTCNN network

Yang Wang; Guowu Yuan D.D.S.; Dong Zheng; Hao Wu; Yuanyuan Pu; Dan Xu

doi:10.1117/12.2539617

14 August 2019 Research on face detection method based on improved MTCNN network

Yang Wang, Guowu Yuan D.D.S., Dong Zheng, Hao Wu, Yuanyuan Pu, Dan Xu

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111791C (2019) https://doi.org/10.1117/12.2539617
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

Abstract

Face detection is one of the important topics in computer vision research and is the basis of many applications. A face detection algorithm based on improved Multi-Task Convolution Neural Network (MTCNN) is proposed in this paper. To increase the accuracy of eye location in complex situations, this method improves the network structure of MTCNN, builds a neural network model based on MTCNN using TensorFlow, and cascades an eye regression network. The Face-Net neural network model was used for training, and the obtained training model was used for detection. Experiments have shown that the accuracy on the LFW dataset is 0.9963 and the accuracy on the YouTube Faces DB dataset is 0.9512.

Citation Download Citation

Yang Wang, Guowu Yuan D.D.S., Dong Zheng, Hao Wu, Yuanyuan Pu, and Dan Xu "Research on face detection method based on improved MTCNN network", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111791C (14 August 2019); https://doi.org/10.1117/12.2539617

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