Occlusion-aware 3D multiple object tracker with two cameras for visual surveillance
dc.contributor.author | Topçu, O. | . |
dc.contributor.author | Alatan, A. A. | |
dc.contributor.author | Ercan, Ali Özer | |
dc.date.accessioned | 2016-02-16T10:26:02Z | |
dc.date.available | 2016-02-16T10:26:02Z | |
dc.date.issued | 2014 | |
dc.identifier.isbn | 978-1-4799-4871-0 | |
dc.identifier.uri | http://hdl.handle.net/10679/2550 | |
dc.identifier.uri | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6918644 | |
dc.description | Due to copyright restrictions, the access to the full text of this article is only available via subscription. | |
dc.description.abstract | An occlusion-aware multiple deformable object tracker for visual surveillance from two cameras is presented. Each object is tracked by a separate particle filter tracker, which is initiated upon detection of a new person and terminated when s/he leaves the scene. Objects are considered as 3D points at their centre of masses as if their mass density is uniform. Point objects and corresponding silhouette centroids in two views together with the epipolar geometry they satisfy resulted in a practical tracking methodology. An occlusion filter is described, that provides the tracker filters conditional occlusion probabilities of the objects, given their estimated positions. Advances over the previous work; in the computation of conditional occlusion probabilities, in incorporation of these probabilities in the particle filter, and in maintaining tracking of separating objects after long periods of moving close-by, are presented on PETS 2006, PETS 2009 and EPFL datasets. | |
dc.language.iso | eng | en_US |
dc.publisher | IEEE | |
dc.relation.ispartof | Advanced Video and Signal Based Surveillance (AVSS), 2014 11th IEEE International Conference on | |
dc.rights | restrictedAccess | |
dc.title | Occlusion-aware 3D multiple object tracker with two cameras for visual surveillance | en_US |
dc.type | Conference paper | en_US |
dc.peerreviewed | yes | |
dc.publicationstatus | published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0003-1126-8259 & YÖK ID 35788) Ercan, Ali | |
dc.contributor.ozuauthor | Ercan, Ali Özer | |
dc.identifier.startpage | 56 | |
dc.identifier.endpage | 61 | |
dc.identifier.wos | WOS:000365607900010 | |
dc.identifier.doi | 10.1109/AVSS.2014.6918644 | |
dc.subject.keywords | Object tracking | |
dc.subject.keywords | Particle filtering (numerical methods) | |
dc.subject.keywords | Probability | |
dc.subject.keywords | Video cameras | |
dc.subject.keywords | Video surveillance | |
dc.identifier.scopus | SCOPUS:2-s2.0-84909953242 | |
dc.contributor.authorMale | 1 | |
dc.relation.publicationcategory | Conference Paper - International - Institutional Academic Staff |
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