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dc.contributor.authorTöreyin, B. Uğuren_US
dc.contributor.authorDedeoğlu, Yiğithanen_US
dc.contributor.authorÇetin, A. Enisen_US
dc.date.accessioned2016-02-08T11:46:27Z
dc.date.available2016-02-08T11:46:27Z
dc.date.issued2006en_US
dc.identifier.issn1-4244-0238-7en_US
dc.identifier.urihttp://hdl.handle.net/11693/27168
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. © 2006 IEEE.en_US
dc.language.isoTurkishen_US
dc.source.title2006 IEEE 14th Signal Processing and Communications Applications Conferenceen_US
dc.relation.isversionofhttps://doi.org/10.1109/SIU.2006.1659753en_US
dc.subjectAudio channel dataen_US
dc.subjectAudio tracksen_US
dc.subjectCCTV surveillance systemsen_US
dc.subjectVideo recording systemsen_US
dc.subjectClosed circuit television systemsen_US
dc.subjectComputer simulationen_US
dc.subjectProblem solvingen_US
dc.subjectVideo recordingen_US
dc.subjectHidden Markov modelsen_US
dc.titleHMM based falling person detection using both audio and videoen_US
dc.title.alternativeSes ve video işaretlerinde sakli markof modeli tabanli düşen kişi tespitien_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.volumeNumber2006en_US
dc.identifier.doi10.1109/SIU.2006.1659753en_US
dc.publisherIEEEen_US


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