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Masked Face Detection Using Deep Learning
Li yichao 1,Qiting Ye 2,Zhao Luo 2,Shiming Ge 2 *
1.School of information engineering Wuhan University of Technology
2.Institute of Information Engineering,Chinese Academy of Sciences
*Correspondence author
#Submitted by
Funding: none
Opened online:28 March 2016
Accepted by: none
Citation: Li yichao,Qiting Ye,Zhao Luo.Masked Face Detection Using Deep Learning[OL]. [28 March 2016] http://en.paper.edu.cn/en_releasepaper/content/4681179
Face occlusion such as masked face is a challenge problem for most face detection algorithms due to a lack of discriminative information. In this paper, we proposed a novel method to address occluded face detection especially masked face detection. We built a masked face database whose images are collected from web images in the wild. The database includes more than 6000 images and more than 10000 masked faces. To perform masked face detection, we proposed a joint pre-detection and classification method, which learn a discriminative classifier based on deep learning to classify the face proposals which are generated by some weak face detectors. The classifier has higher discrimination power to masked face, unmasked face and non-face. Experimental comparisons with state-of-the-art face detection methods show that the proposed method can give better performance. .
Keywords:Image Processing;Occlusion Face Detection;Deep Learning;Convolutional Neural Network

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