제어로봇시스템학회논문지 (Journal of Institute of Control, Robotics and Systems)

  • 제19권6호
  • /
  • Pages.513-519
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  • 2013
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  • 1976-5622(pISSN)
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  • 2233-4335(eISSN)
제어로봇시스템학회 (Institute of Control, Robotics and Systems)
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생리적 내재반응 및 얼굴표정 간 확률 관계 모델 기반의 감정인식 시스템에 관한 연구

A Study on Emotion Recognition Systems based on the Probabilistic Relational Model Between Facial Expressions and Physiological Responses

  • 고광은 (중앙대학교 전자전기공학부) ;
  • 심귀보 (중앙대학교 전자전기공학부)
  • Ko, Kwang-Eun (School of Electrical and Electronics Engineering, Chung-Ang University) ;
  • Sim, Kwee-Bo (School of Electrical and Electronics Engineering, Chung-Ang University)
  • 투고 : 2013.03.25
  • 심사 : 2013.04.29
  • 발행 : 2013.06.01
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초록

The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

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참고문헌

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