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By A. Punitha and M. Kalaiselvi Geetha


The most expressive way humans display emotions is through facial expressions. The aim of facial expression recognition methods is to build a system for classification of facial expressions from continuous video input automatically. The method proposed by Viola and Jones is used to detect the face region. Since the mouth plays a vital role in expressing emotions, the mouth features are used for classifying expressions. The mouth intensity code value (MICV) extracted from the mouth region is used as a feature in this work. This MICV difference between the first and the greatest facial expression intensity frame is used as an input to a Hidden Markov Model (HMM) to recognize facial expression

Topics: HMM
Year: 2014
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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