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Facial expression recognition and expression intensity estimation
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Yang, Peng. Facial expression recognition and expression intensity estimation. Retrieved from https://doi.org/doi:10.7282/T3CN736N

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TitleFacial expression recognition and expression intensity estimation
NameYang, Peng (author); Metaxas, Dimitris (chair); Elgammal, Ahmed (internal member); Pavlovic, Vladimir (internal member); Tian, Yingli (outside member); Rutgers University; Graduate School - New Brunswick
Date Created2011
Other Date2011-05 (degree)
SubjectComputer Science, Facial expression, Facial expression—Testing, Computer vision
Extentxi, 88 p. : ill.
DescriptionSeventy years ago, psychologist categorized the facial expression into seven categories: angry, disgust, fear, happiness, sadness, surprise and neutral. Through analyzing the expression, psychologists want to predict the emotions behind the expression. Due to all kinds of potential applications on human emotion analysis, automatical analysis of human affective expressions has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. Researchers have done lots of works on this topic in the past thirty years, and proposed lots of promising approaches. Although many works have been done on this topic, these existing methods typically handle deliberately displayed and exaggerated expression of prototypical emotions. There are still some hard problems not solved well for the real system to handle naturally occurring emotions such as exploring discriminative features, time wrapping, and expression intensity estimation. Our work focuses on these real problems, analyzes the challenges in the real system and proposes the sounded solutions for advancing human affect sensing technology.
NotePh.D.
NoteIncludes bibliographical references
NoteIncludes vita
Noteby Peng Yang
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/T3CN736N
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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