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학술대회 Real-Time Personalized Facial Expression Recognition System based on Deep Learning
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이인재, 정희철, 안충현, 서정일, 김준모, 권오석
International Conference on Consumer Electronics (ICCE) 2016, pp.267-268
15MR3200, (통합)방송용 영상 인식 기반 객체 중심 지식 융합 미디어 서비스 플랫폼 개발, 조기성
Over the last few years, deep learning has produced breakthrough results in many application fields including speech recognition, image understanding and so on. We try to deep learning techniques for real-time facial expression recognition instead of hand-crafted feature-based methods. The proposed system can recognize human emotions based on facial expressions using a webcam. It can detect faces and recognize users with a distance of 2~3m for TV environment. And it can determine whether a user is feeling happiness, sadness, surprise, anger, disgust, neutral or any combination of those six emotions. The experimental results show that the proposed method achieves high accuracy. It can be used for various services such as consumer behavior research, usability studies, psychology, educational research, and market research.
KSP 제안 키워드
Application fields, Behavior research, Consumer behavior, Facial Expression Recognition(FER), Facial expression recognition system, Feature-based methods, Hand-crafted feature, High accuracy, Human Emotions, Market Research, Real-Time