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학술대회 Development of Deep Learning-Based Facial Expression Recognition System
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정희철, 이시행, 박선정, 김병주, 김준모, 이인재, 안충현
Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV) 2015, pp.1-4
14MR1400, 감성 기반 사용자 맞춤형 UI/UX 방송시스템 기술개발, 안충현
Deep learning is considered to be a breakthrough in the field of computer vision, since most of the world records of the recognition tasks are being broken. In this paper, we try to apply such deep learning techniques to recognizing facial expressions that represent human emotions. The procedure of our facial expression recognition system is as follows: First, face is detected from input image using Haar-like features. Second, the deep network is used for recognizing facial expression using detected faces. In this step, two different deep networks can be used such as deep neural network and convolutional neural network. Consequently, we compared experimentally two types of deep networks, and the convolutional neural network had better performance than deep neural network.
convolutional neural network, deep learning, deep neural network, Facial expression recognition
KSP 제안 키워드
Computer Vision(CV), Convolution neural network(CNN), Deep neural network(DNN), Facial Expression Recognition(FER), Facial expression recognition system, Haar-Like features, Human Emotions, Learning-based, deep learning(DL), deep networks