Bimodal face and body gesture database for automatic analysis of human nonverbal affective behavior

Gunes, H; Piccardi, M

Bimodal face and body gesture database for automatic analysis of human nonverbal affective behavior

Gunes, H Piccardi, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings - International Conference on Pattern Recognition, 2006, 1 pp. 1148 - 1153
Issue Date:: 2006-12-01

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Field	Value	Language
dc.contributor.author	Gunes, H	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.date.issued	2006-12-01	en_US
dc.identifier.citation	Proceedings - International Conference on Pattern Recognition, 2006, 1 pp. 1148 - 1153	en_US
dc.identifier.isbn	0769525210	en_US
dc.identifier.isbn	9780769525211	en_US
dc.identifier.issn	1051-4651	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2540
dc.description.abstract	To be able to develop and test robust affective multimodal systems, researchers need access to novel databases containing representative samples of human multi-modal expressive behavior. The creation of such databases requires a major effort in the definition of representative behaviors, the choice of expressive modalities, and the collection and labeling of large amount of data. At present, public databases only exist for single expressive modalities such as facial expression analysis. There also exist a number of gesture databases of static and dynamic hand postures and dynamic hand gestures. However, there is not a readily available database combining affective face and body information in a genuine bimodal manner. Accordingly, in this paper, we present a bimodal database recorded by two high-resolution cameras simultaneously for use in automatic analysis of human nonverbal affective behavior. © 2006 IEEE.	en_US
dc.relation.ispartof	Proceedings - International Conference on Pattern Recognition	en_US
dc.relation.isbasedon	10.1109/ICPR.2006.39	en_US
dc.title	Bimodal face and body gesture database for automatic analysis of human nonverbal affective behavior	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1	en_US
utslib.for	080104 Computer Vision	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Hong Kong, China	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

Abstract:

To be able to develop and test robust affective multimodal systems, researchers need access to novel databases containing representative samples of human multi-modal expressive behavior. The creation of such databases requires a major effort in the definition of representative behaviors, the choice of expressive modalities, and the collection and labeling of large amount of data. At present, public databases only exist for single expressive modalities such as facial expression analysis. There also exist a number of gesture databases of static and dynamic hand postures and dynamic hand gestures. However, there is not a readily available database combining affective face and body information in a genuine bimodal manner. Accordingly, in this paper, we present a bimodal database recorded by two high-resolution cameras simultaneously for use in automatic analysis of human nonverbal affective behavior. © 2006 IEEE.

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