Deep Convolution Neural Networks for Automatic Eyeglasses Removal

MAO LIANG, YUEJU XUE, KUNNAN XUE, AQING YANG

Abstract


The facial image under eyeglasses occlusion can degrade face recognition performance. Inspired by the success of deep convolutional neural networks (DCNN) on super resolution, in this paper, a method based on deep convolutional neural network is developed for automatic eyeglasses removal from frontal facial images. To remove eyeglasses on facial images, the proposed approach applied deep convolution neural networks (end-to-end DCNN) to reconstruct the eyeglasses region. We adopt the deep convolutional neural networks (DCNN) approach is designed and trained to learn the mapping between pairs of face images with or without eyeglasses from a large face database in video surveillance. The extensive experiments show that the proposed algorithm can effectively remove eyeglasses, and also can keep the stability of face recognition under eyeglasses on occlusion.

Keywords


Eyeglasses Removal, Deep Convolutional Neural Network, Face Recognition


DOI
10.12783/dtcse/aiea2017/14988

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