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An automatic method for motion capture-based exaggeration of facial expressions with personality types

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Abstract

Facial expressions have always attracted considerable attention as a form of nonverbal communication. In visual applications such as movies, games, and animations, people tend to be interested in exaggerated expressions rather than regular expressions since the exaggerated ones deliver more vivid emotions. In this paper, we propose an automatic method for exaggeration of facial expressions from motion-captured data with a certain personality type. The exaggerated facial expressions are generated by using the exaggeration mapping (EM) that transforms facial motions into exaggerated motions. As all individuals do not have identical personalities, a conceptual mapping of the individual’s personality type for exaggerating facial expressions needs to be considered. The Myers–Briggs type indicator, which is a popular method for classifying personality types, is employed to define the personality-type-based EM. Further, we have experimentally validated the EM and simulations of facial expressions.

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Acknowledgments

This research was partially supported by the Korea Research Foundation Grant fund (KRF-521-D00398).

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Authors and Affiliations

  1. Division of Multimedia, College of Engineering, Sungkyul University, Anyang, South Korea

    Seongah Chin

  2. Biointelligence Laboratory, School of Computer Science and Engineering, Seoul National University, Seoul, South Korea

    Chung Yeon Lee

  3. DXP Lab., Department of Computer Science, College of Engineering, Korea University, Seoul, South Korea

    Jaedong Lee

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  1. Seongah Chin
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  2. Chung Yeon Lee
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  3. Jaedong Lee
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Correspondence to Seongah Chin.

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Chin, S., Lee, C.Y. & Lee, J. An automatic method for motion capture-based exaggeration of facial expressions with personality types. Virtual Reality 17, 219–237 (2013). https://doi.org/10.1007/s10055-013-0227-8

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