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dc.contributor.authorZhou, Zhongnaeng
dc.contributor.authorChen, Xieng
dc.contributor.authorChung, Yu-Chia, 1979-eng
dc.contributor.authorHe, Zhihai, 1973-eng
dc.contributor.authorHan, Tony X.eng
dc.contributor.authorKeller, James M.eng
dc.date.issued2008-11eng
dc.descriptionDOI 10.1109/TCSVT.2008.2005612eng
dc.description.abstractIn this work, we study how continuous video monitoring and intelligent video processing can be used in eldercare to assist the independent living of elders and to improve the efficiency of eldercare practice. More specifically, we develop an automated activity analysis and summarization for eldercare video monitoring. At the object level, we construct an advanced silhouette extraction, human detection and tracking algorithm for indoor environments. At the feature level, we develop an adaptive learning method to estimate the physical location and moving speed of a person from a single camera view without calibration. At the action level, we explore hierarchical decision tree and dimension reduction methods for human action recognition. We extract important ADL (activities of daily living) statistics for automated functional assessment. To test and evaluate the proposed algorithms and methods, we deploy the camera system in a real living environment for about a month and have collected more than 200 hours (in excess of 600 G bytes) of activity monitoring videos. Our extensive tests over these massive video datasets demonstrate that the proposed automated activity analysis system is very efficient.eng
dc.description.sponsorshipThis work was supported in part by National Institute of Health under Grant 5R21AG026412.eng
dc.identifier.citationIEEE Transactions on Circuits and Systems for Video Technology, VOL. 18, NO. 11, November 2008.eng
dc.identifier.issn1051-8215eng
dc.identifier.urihttp://hdl.handle.net/10355/9260eng
dc.languageEnglisheng
dc.publisherIEEEeng
dc.relation.ispartofComputer and Electrical Engineering publications (MU)eng
dc.relation.ispartofcommunityUniversity of Missouri-Columbia. College of Engineering. Department of Electrical and Computer Engineeringeng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.eng
dc.source.harvestedIEEEXploreeng
dc.subject.lcshOlder people -- Care -- Technological innovationseng
dc.subject.lcshVideo surveillanceeng
dc.subject.lcshLife care communitieseng
dc.titleActivity Analysis, Summarization, and Visualization for Indoor Human Activity Monitoringeng
dc.typeArticleeng


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