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http://dx.doi.org/10.5391/JKIIS.2005.15.5.573

Face Emotion Recognition by Fusion Model based on Static and Dynamic Image  

Lee Dae-Jong (Chungbuk National University School of Electrical and Computer Engineering)
Lee Kyong-Ah (Dasan Networks)
Go Hyoun-Joo (Chungbuk National University School of Electrical and Computer Engineering)
Chun Myung-Geun (Chungbuk National University School of Electrical and Computer Engineering)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.15, no.5, 2005 , pp. 573-580 More about this Journal
Abstract
In this paper, we propose an emotion recognition using static and dynamic facial images to effectively design human interface. The proposed method is constructed by HMM(Hidden Markov Model), PCA(Principal Component) and wavelet transform. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition in the static images is performed by using the discrete wavelet. Here, the feature vectors are extracted by using PCA. Emotion recognition in the dynamic images is performed by using the wavelet transform and PCA. And then, those are modeled by the HMM. Finally, we obtained better performance result from merging the recognition results for the static images and dynamic images.
Keywords
Emotion Recognition; Wavelet Transform; HMM(hidden markov model); Principal Component Analysis;
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