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dc.contributor.authorTöreyin, U. B.en_US
dc.contributor.authorDedeğlu, Y.en_US
dc.contributor.authorÇetin, A. Enisen_US
dc.date.accessioned2016-02-08T11:49:55Z
dc.date.available2016-02-08T11:49:55Z
dc.date.issued2005en_US
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/11693/27290
dc.description.abstractAutomatic detection of a falling person in video is an important problem with applications in security and safety areas including supportive home environments and CCTV surveillance systems. Human motion in video is modeled using Hidden Markov Models (HMM) in this paper. In addition, the audio track of the video is also used to distinguish a person simply sitting on a floor from a person stumbling and falling. Most video recording systems have the capability of recording audio as well and the impact sound of a falling person is also available as an additional clue. Audio channel data based decision is also reached using HMMs and fused with results of HMMs modeling the video data to reach a final decision.en_US
dc.language.isoEnglishen_US
dc.source.titleLecture Notes in Computer Scienceen_US
dc.relation.isversionofhttps://doi.org/10.1007/11573425_21en_US
dc.titleHMM based falling person detection using both audio and videoen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage211en_US
dc.citation.epage220en_US
dc.citation.volumeNumber3766en_US
dc.identifier.doi10.1007/11573425_21en_US
dc.publisherSpringeren_US
dc.contributor.bilkentauthorÇetin, A. Enis
dc.identifier.eissn1611-3349


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