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ICASSP
2010
IEEE

Visual emotion recognition using compact facial representations and viseme information

10 years 3 months ago
Visual emotion recognition using compact facial representations and viseme information
Emotion expression is an essential part of human interaction. Rich emotional information is conveyed through the human face. In this study, we analyze detailed motion-captured facial information of ten speakers of both genders during emotional speech. We derive compact facial representations using methods motivated by Principal Component Analysis and speaker face normalization. Moreover, we model emotional facial movements by conditioning on knowledge of speech-related movements (articulation). We achieve average classi cation accuracies on the order of 75% for happiness, 50-60% for anger and sadness and 35% for neutrality in speaker independent experiments. We also nd that dynamic modeling and the use of viseme information improves recognition accuracy for anger, happiness and sadness, as well as for the overall unweighted performance.
Angeliki Metallinou, Carlos Busso, Sungbok Lee, Sh
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where ICASSP
Authors Angeliki Metallinou, Carlos Busso, Sungbok Lee, Shrikanth Narayanan
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