DocumentCode :
3186554
Title :
Veering around the Uncanny Valley: Revealing the underlying structure of facial expressions
Author :
Mones, Barbara ; Friedman, Stephen
Author_Institution :
Comput. Sci. & Eng., Univ. of Washington, Seattle, WA, USA
fYear :
2011
fDate :
21-25 March 2011
Firstpage :
345
Lastpage :
345
Abstract :
Summary form only given: When designing both realistic and stylized virtual characters, it is critical to avoid the Uncanny Valley so that visual communication can be consistent, compelling and believable. The human ability to recognize and interpret facial expression as emotion is one of our most sophisticated and innate perceptual skills. This skill is so critical to our life as social creatures that there seem to be multiple neural paths for analyzing faces, a “fine mesh” system for analyzing realistic faces, and a “coarse mesh” system for interpreting human faces seen under difficult viewing conditions, or stylized faces. The fine mesh system relies primarily on analyzing tiny deflections from precise facial norms, while the coarse mesh seems to use pattern recognition rather than position mapping. Certain patterns seem to “trigger” recognition that a certain expression is present.
Keywords :
character recognition; emotion recognition; face recognition; virtual reality; Amazon mechanical turk; animated character; coarse mesh trigger detection; computer workstation; expression vocabulary; facial expression; human face analysis; human perception; multiple neural paths; pattern recognition; position mapping; social creature; stylized character; trigger recognition; uncanny valley; virtual characters; visual communication; Computer science; Face recognition; Facial animation; Humans; Visual communication; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
978-1-4244-9140-7
Type :
conf
DOI :
10.1109/FG.2011.5771423
Filename :
5771423
Link To Document :
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