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Facial Expression Hallucination

2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1, 2005
Given a person's neutral face image, we can predict his/her expressive face images by machine learning techniques. Different from the prior expression cloning or image analogy approaches, we try to hallucinate the person's plausible facial expression with the help of a face expression database.
Congyong Su, Li Huang
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Rapport and facial expression

2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, 2009
How to build virtual agents that establish rapport with human? According to Tickle-Degnen and Rosenthal [4], the three essential components of rapport are mutual attentiveness, positivity and coordination. In our previous work, we designed an embodied virtual agent to establish rapport with a human speaker by providing rapid and contingent nonverbal ...
Ning Wang 0012, Jonathan Gratch
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Facial Reactions to Facial Expressions

Psychophysiology, 1982
ABSTRACTPrevious research has demonstrated that different patterns of facial muscle activity are correlated with different emotional states. In the present study subjects were exposed to pictures of happy and angry facial expressions, in response to which their facial electromyographic (EMG) activities, heart rate (HR), and palmar skin conductance ...
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Emotion and Facial Expression

2000
Facial expression is usually synthesized or predicted on the basis of a given emotion. The prototypical expressions for basic emotions (happiness, sadness, surprise, disgust, anger, and fear) as postulated by discrete emotion psychologists are rather consistently produced and interpreted among different cultures, and can be used as icons to represent a
Thomas Wehrle, Susanne Kaiser
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FACIAL EXPRESSION AND SARCASM

Perceptual and Motor Skills, 2001
This study examined facial expression in the presentation of sarcasm. 60 responses (sarcastic responses = 30, nonsarcastic responses = 30) from 40 different speakers were coded by two trained coders. Expressions in three facial areas—eyebrow, eyes, and mouth—were evaluated. Only movement in the mouth area significantly differentiated ratings of sarcasm
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Facial expression decomposition

Proceedings Ninth IEEE International Conference on Computer Vision, 2003
In this paper, we propose a novel approach for facial expression decomposition - higher-order singular value decomposition (HOSVD), a natural generalization of matrix SVD. We learn the expression subspace and person subspace from a corpus of images showing seven basic facial expressions, rather than resort to expert-coded facial expression parameters ...
Hongcheng Wang, Narendra Ahuja
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Caricaturing facial expressions

Cognition, 2000
The physical differences between facial expressions (e.g. fear) and a reference norm (e.g. a neutral expression) were altered to produce photographic-quality caricatures. In Experiment 1, participants rated caricatures of fear, happiness and sadness for their intensity of these three emotions; a second group of participants rated how 'face-like' the ...
A J, Calder   +5 more
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Facial Pain Expression

Pain Management, 2011
SUMMARY People in pain communicate their experience via facial expressions. There has been considerable research into the properties of pain expressions. This article reviews basic findings on the encoding and decoding of pain expression. The facial expression of pain is characterized and recent findings on its assessment and psychometric properties ...
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Facial expression recognition

2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2005
The paper aims at recognizing the various human facial expressions. Every countenance is marked by changes in the feature points of the face. These feature points are located in various regions of the face. There are two phases in the facial expression recognition technique described here.
P.K. Manglik   +3 more
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Manifold of facial expression

2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443), 2004
We propose the concept of manifold of facial expression based on the observation that images of a subject's facial expressions define a smooth manifold in the high dimensional image space. Such a manifold representation can provide a unified framework for facial expression analysis.
Ya Chang, Changbo Hu, Matthew Turk 0001
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