Human activity analysis for geriatric care in nursing homes

Chen, MY; Hauptmann, A; Bharucha, A; Wactlar, H; Yang, Y

Human activity analysis for geriatric care in nursing homes

Chen, MY Hauptmann, A Bharucha, A Wactlar, H Yang, Y

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Publication Type:: Conference Proceeding
Citation:: 2013, 9781461435013 pp. 53 - 61
Issue Date:: 2013-10-01

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Field	Value	Language
dc.contributor.author	Chen, MY	en_US
dc.contributor.author	Hauptmann, A	en_US
dc.contributor.author	Bharucha, A	en_US
dc.contributor.author	Wactlar, H	en_US
dc.contributor.author	Yang, Y https://orcid.org/0000-0001-5528-0546	en_US
dc.date.issued	2013-10-01	en_US
dc.identifier.citation	2013, 9781461435013 pp. 53 - 61	en_US
dc.identifier.isbn	1461435005	en_US
dc.identifier.isbn	9781461435006	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119457
dc.description.abstract	© 2013 Springer Science+Business Media, LLC. All rights reserved. As our society is increasingly aging, it is urgent to develop computer aided techniques to improve the quality-of-care (QoC) and quality-of-life (QoL) of geriatric patients. In this paper, we focus on automatic human activities analysis in video surveillance recorded in complicated environments at a nursing home. This will enable the automatic exploration of the statistical patterns between patients' daily activities and their clinical diagnosis. We also discuss potential future research directions in this area. Experiment demonstrate the proposed approach is effective for human activity analysis.	en_US
dc.relation.isbasedon	10.1007/978-1-4614-3501-3_5	en_US
dc.title	Human activity analysis for geriatric care in nursing homes	en_US
dc.type	Conference Proceeding
utslib.citation.volume	9781461435013	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	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/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	9781461435013	en_US

Abstract:

© 2013 Springer Science+Business Media, LLC. All rights reserved. As our society is increasingly aging, it is urgent to develop computer aided techniques to improve the quality-of-care (QoC) and quality-of-life (QoL) of geriatric patients. In this paper, we focus on automatic human activities analysis in video surveillance recorded in complicated environments at a nursing home. This will enable the automatic exploration of the statistical patterns between patients' daily activities and their clinical diagnosis. We also discuss potential future research directions in this area. Experiment demonstrate the proposed approach is effective for human activity analysis.

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http://hdl.handle.net/10453/119457