지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2014.10
- 수록면
- 804 - 807 (4page)
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초록· 키워드
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In this paper, a temporal-reinforced approach to enhancing emotion recognition from facial images is presented. Shape and texture models of facial images are computed by using active appearance model (AAM), from which facial feature points and geometrical feature values are extracted. The extracted features are used by relevance vector machine (RVM) to recognize emotional states. We propose a temporal analysis approach to recognizing likelihood of emotional categories, such that more subtle emotion, such as degree and ratio of basic emotional states can be obtained. Furthermore, a method is developed to map the recognition result to the arousal-valence plane (A-V Plane). Experimental results verify that the performance of emotion recognition is enhanced by the proposed method.
목차
Abstract
1. INTRODUCTION
2. FEATURE EXTRACTION
3. PROPOSED INTERACTIVE EMOTION RECOGNITION ALGORITHM
4. EXPERIMENTAL RESULT
5. CONCLUSIONS AND FUTURE WORK
REFERENCES
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