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Adaptive Facial Expression Recognition System based on Gabor Wavelet Neural Network

가버 웨이블릿 신경망 기반 적응 표정인식 시스템

  • 이상완 (한국과학기술원 전자전산학과) ;
  • 김대진 (한국과학기술원 인간친화 복지 로봇 시스템 연구센터) ;
  • 김용수 (대전대학교 컴퓨터 공학부) ;
  • 변증남 (한국과학기술원 전자전산학과)
  • Published : 2006.02.01

Abstract

In this paper, adaptive Facial Emotional Recognition system based on Gabor Wavelet Neural Network, considering six feature Points in face image to extract specific features of facial expression, is proposed. Levenberg-Marquardt-based training methodology is used to formulate initial network, including feature extraction stage. Therefore, heuristics in determining feature extraction process can be excluded. Moreover, to make an adaptive network for new user, Q-learning which has enhanced reward function and unsupervised fuzzy neural network model are used. Q-learning enables the system to ge optimal Gabor filters' sets which are capable of obtaining separable features, and Fuzzy Neural Network enables it to adapt to the user's change. Therefore, proposed system has a good on-line adaptation capability, meaning that it can trace the change of user's face continuously.

References

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