The Journal of Korean Institute of Communications and Information Sciences (한국통신학회논문지)

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Local Feature Based Facial Expression Recognition Using Adaptive Decision Tree

적응형 결정 트리를 이용한 국소 특징 기반 표정 인식

  • 오지훈 (연세대학교 전기전자공학과 영상 및 비디오 패턴 인식 연구실) ;
  • 반유석 (연세대학교 전기전자공학과 영상 및 비디오 패턴 인식 연구실) ;
  • 이인재 (한국전자통신연구원) ;
  • 안충현 (한국전자통신연구원) ;
  • 이상윤 (연세대학교 전기전자공학과 영상 및 비디오 패턴 인식 연구실)
  • Received : 2013.01.13
  • Accepted : 2014.02.03
  • Published : 2014.02.28
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Abstract

This paper proposes the method of facial expression recognition based on decision tree structure. In the image of facial expression, ASM(Active Shape Model) and LBP(Local Binary Pattern) make the local features of a facial expressions extracted. The discriminant features gotten from local features make the two facial expressions of all combination classified. Through the sum of true related to classification, the combination of facial expression and local region are decided. The integration of branch classifications generates decision tree. The facial expression recognition based on decision tree shows better recognition performance than the method which doesn't use that.

본 논문은 결정 트리(Decision tree) 구조를 기반으로 한 표정 인식 방법을 제안한다. ASM(Active Shape Model)과 LBP(Local Binary Pattern)를 통해, 표정 영상들의 국소 특징들을 추출한다. 국소 특징들로부터 표정들을 잘 분류할 수 있는 판별 특징(Discriminant feature)들을 추출하고, 그 판별 특징들은 모든 조합의 각 두 가지 표정들을 분류시킨다. 분류를 통해 얻어진 정인식의 합을 통해, 정인식 최대화 기반 국소 영역과 표정 조합을 결정한다. 이 가지 분류들을 종합하여, 결정 트리를 생성한다. 이 결정 트리 기반 표정 인식률은 약 84.7%로, 결정 트리를 고려하지 않은 방법보다, 더 좋은 인식 성능을 보였다.

Keywords

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