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http://dx.doi.org/10.3745/KIPSTB.2006.13B.7.653

Emotion Recognition Based on Facial Expression by using Context-Sensitive Bayesian Classifier  

Kim, Jin-Ok (대구한의대학교 정보경영대학 모바일콘텐츠학부)
Publication Information
The KIPS Transactions:PartB / v.13B, no.7, 2006 , pp. 653-662 More about this Journal
Abstract
In ubiquitous computing that is to build computing environments to provide proper services according to user's context, human being's emotion recognition based on facial expression is used as essential means of HCI in order to make man-machine interaction more efficient and to do user's context-awareness. This paper addresses a problem of rigidly basic emotion recognition in context-sensitive facial expressions through a new Bayesian classifier. The task for emotion recognition of facial expressions consists of two steps, where the extraction step of facial feature is based on a color-histogram method and the classification step employs a new Bayesian teaming algorithm in performing efficient training and test. New context-sensitive Bayesian learning algorithm of EADF(Extended Assumed-Density Filtering) is proposed to recognize more exact emotions as it utilizes different classifier complexities for different contexts. Experimental results show an expression classification accuracy of over 91% on the test database and achieve the error rate of 10.6% by modeling facial expression as hidden context.
Keywords
Facial Expression Recognition; Emotion Recognition; Bayesian Classifier; HCI;
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Times Cited By KSCI : 1  (Citation Analysis)
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