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Study of Emotion Recognition based on Facial Image for Emotional Rehabilitation Biofeedback

정서재활 바이오피드백을 위한 얼굴 영상 기반 정서인식 연구

  • 고광은 (중앙대학교 전자전기공학부) ;
  • 심귀보 (중앙대학교 전자전기공학부)
  • Received : 2010.06.10
  • Accepted : 2010.07.20
  • Published : 2010.10.01

Abstract

If we want to recognize the human's emotion via the facial image, first of all, we need to extract the emotional features from the facial image by using a feature extraction algorithm. And we need to classify the emotional status by using pattern classification method. The AAM (Active Appearance Model) is a well-known method that can represent a non-rigid object, such as face, facial expression. The Bayesian Network is a probability based classifier that can represent the probabilistic relationships between a set of facial features. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with FACS (Facial Action Coding System) for automatically modeling and extracting the facial emotional features. To recognize the facial emotion, we use the DBNs (Dynamic Bayesian Networks) for modeling and understanding the temporal phases of facial expressions in image sequences. The result of emotion recognition can be used to rehabilitate based on biofeedback for emotional disabled.

Acknowledgement

Supported by : 한국연구재단

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Cited by

  1. A Study on Emotion Recognition Systems based on the Probabilistic Relational Model Between Facial Expressions and Physiological Responses vol.19, pp.6, 2013, https://doi.org/10.5302/J.ICROS.2013.13.1900