Mean Shift Based Object Tracking Supported with Adaptive Kalman Filter

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dc.authoridHanbay, Davut/0000-0003-2271-7865
dc.authoridTURHAN, Mehmet Murat/0000-0003-4497-9102
dc.authorwosidHanbay, Davut/AAG-8511-2019
dc.contributor.authorTurhan, Mehmet Murat
dc.contributor.authorHanbay, Davut
dc.date.accessioned2024-08-04T20:41:07Z
dc.date.available2024-08-04T20:41:07Z
dc.date.issued2015
dc.departmentİnönü Üniversitesien_US
dc.description23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYen_US
dc.description.abstractIn this paper, mean shift algorithm and adaptive Kalman filter have been both utilized to realize object tracking in video sequences. Mean shift algorithm cannot give good results when the position of the tracked object is changed rapidly between sequential frames or the tracked object is occluded. In this paper, the first position of the tracked object is predicted by Kalman filter then mean shift algorithm starts to seek the object in this position. Bhattacharyya coefficient which is obtained from mean shift algorithm, is used to instantly update Kalman filters error covariance matrix and determine whether object is occluded or not. Experimental results demonstrate that the proposed method has been more efficient technique as compared to standard mean shift algorithm in case of occlusion and fast object tracking.en_US
dc.description.sponsorshipDept Comp Engn & Elect & Elect Engn,Elect & Elect Engn,Bilkent Univen_US
dc.identifier.endpage2673en_US
dc.identifier.isbn978-1-4673-7386-9
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-84939202885en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage2670en_US
dc.identifier.urihttps://hdl.handle.net/11616/96921
dc.identifier.wosWOS:000380500900652en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2015 23rd Signal Processing and Communications Applications Conference (Siu)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectObject Trackingen_US
dc.subjectMean Shift Algorithmen_US
dc.subjectAdaptive Kalman Filteren_US
dc.titleMean Shift Based Object Tracking Supported with Adaptive Kalman Filteren_US
dc.typeConference Objecten_US

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