Extracting key postures in a human action video sequence

Chen, Y; Wu, Q; He, X; Du, C; Yang, J

Extracting key postures in a human action video sequence

Chen, Y Wu, Q

He, X

Du, C Yang, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008, 2008, pp. 569 - 573
Issue Date:: 2008-12-31

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Field	Value	Language
dc.contributor.author	Chen, Y	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Du, C	en_US
dc.contributor.author	Yang, J	en_US
dc.date.issued	2008-12-31	en_US
dc.identifier.citation	Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008, 2008, pp. 569 - 573	en_US
dc.identifier.isbn	9781424422951	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10939
dc.description.abstract	Human key posture extraction from videos will benefit video storage, video retrieval, human action recognition, human behaviour understanding and so on. This paper presents an approach to select key postures from human action sequences using 2D information. There are two steps in the proposed method. Information measurement which is a kind of global feature of a frame is used to roughly find key posture candidates. Then, a body skeleton feature which is a kind of local feature is applied to select final key postures from the candidates obtained in the first step. The experiments show that the proposed method is efficient. © 2008 IEEE.	en_US
dc.relation.ispartof	Proceedings of the 2008 IEEE 10th Workshop on Multimedia Signal Processing, MMSP 2008	en_US
dc.relation.isbasedon	10.1109/MMSP.2008.4665142	en_US
dc.title	Extracting key postures in a human action video sequence	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Cairns, Queensland, Australia	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/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Human key posture extraction from videos will benefit video storage, video retrieval, human action recognition, human behaviour understanding and so on. This paper presents an approach to select key postures from human action sequences using 2D information. There are two steps in the proposed method. Information measurement which is a kind of global feature of a frame is used to roughly find key posture candidates. Then, a body skeleton feature which is a kind of local feature is applied to select final key postures from the candidates obtained in the first step. The experiments show that the proposed method is efficient. © 2008 IEEE.

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http://hdl.handle.net/10453/10939