A hybrid tracking method for scaled and oriented objects in crowded scenes

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dc.authoridTalu, Muhammed Fatih/0000-0003-1166-8404
dc.authoridTURKOGLU, IBRAHIM/0000-0003-4938-4167
dc.authoridCebeci, Mehmet/0000-0002-2971-6788
dc.authorwosidCebeci, Mehmet/AAB-6297-2020
dc.authorwosidTalu, Muhammed Fatih/W-2834-2017
dc.authorwosidTURKOGLU, IBRAHIM/A-2640-2016
dc.contributor.authorTalu, M. Fatih
dc.contributor.authorTurkoglu, Ibrahim
dc.contributor.authorCebeci, Mehmet
dc.date.accessioned2024-08-04T20:32:53Z
dc.date.available2024-08-04T20:32:53Z
dc.date.issued2011
dc.departmentİnönü Üniversitesien_US
dc.description.abstractTraditional kernel based means shift assumes constancy of the object scale and orientation during the course of tracking and uses a symmetric/asymmetric kernel, such as a circle or an ellipse for target representation. In a tracking scenario, it is not uncommon to observe objects with complex shapes whose scale and orientation constantly change due to the camera and object motions. In this paper, we propose a multi object tracking method which tracks the complete object regions, adapts to changing scale and orientation, and assigns consistent labels to each object throughout real world video sequences. Our approach has five major components: (1) dynamic background subtraction, (2) level sets, (3) mean shift convergence, (4) object identification, and (5) occlusion handling. The experimental results show that the proposed method is superior to the traditional mean shift tracking in the following aspects: (1) it provides consistent multi objects tracking instead of single object throughout the video, (2) it is not affected by the scale and orientation changes of the tracked objects, (3) its computational complexity is much less than traditional mean shift due to using level set method instead of probability density. (C) 2011 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.eswa.2011.04.153
dc.identifier.endpage13687en_US
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.issue11en_US
dc.identifier.scopus2-s2.0-79959945869en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage13682en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2011.04.153
dc.identifier.urihttps://hdl.handle.net/11616/95371
dc.identifier.volume38en_US
dc.identifier.wosWOS:000294084700020en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMulti object trackingen_US
dc.subjectBackground subtractionen_US
dc.subjectMean shiften_US
dc.subjectLevel set methodsen_US
dc.subjectOcclusion handlingen_US
dc.titleA hybrid tracking method for scaled and oriented objects in crowded scenesen_US
dc.typeArticleen_US

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