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dc.contributor.authorBaysal, S.en_US
dc.contributor.authorDuygulu, P.en_US
dc.date.accessioned2018-04-12T10:42:37Z
dc.date.available2018-04-12T10:42:37Z
dc.date.issued2016en_US
dc.identifier.issn1051-8215
dc.identifier.urihttp://hdl.handle.net/11693/36506
dc.description.abstractTracking multiple players is crucial to analyze soccer videos in real time. Yet, rapid illumination changes and occlusions among players who look similar from a distance make tracking in soccer very difficult. Particle-filter-based approaches have been utilized for their ability in tracking under occlusion and rapid motions. Unlike the common practice of choosing particles on targets, we introduce the notion of shared particles densely sampled at fixed positions on the model field. We globally evaluate targets' likelihood of being on the model field particles using our combined appearance and motion model. This allows us to encapsulate the interactions among the targets in the state-space model and track players through challenging occlusions. The proposed tracking algorithm is embedded into a real-life soccer player tracking system called Sentioscope. We describe the complete steps of the system and evaluate our approach on large-scale video data gathered from professional soccer league matches. The experimental results show that the proposed algorithm is more successful, compared with the previous methods, in multiple-object tracking with similar appearances and unpredictable motion patterns such as in team sports. © 1991-2012 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.titleIEEE Transactions on Circuits and Systems for Video Technologyen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/TCSVT.2015.2455713en_US
dc.subjectModel field particlesen_US
dc.subjectMultiple-object trackingen_US
dc.subjectSentioscopeen_US
dc.subjectSoccer player trackingen_US
dc.subjectSports video analysisen_US
dc.subjectMotion analysisen_US
dc.subjectMotion estimationen_US
dc.subjectState space methodsen_US
dc.subjectTracking (position)en_US
dc.subjectIllumination changesen_US
dc.subjectMultiple object trackingen_US
dc.subjectParticle filteren_US
dc.subjectSentioscopeen_US
dc.subjectSoccer playeren_US
dc.subjectSports video analysisen_US
dc.subjectState - space modelsen_US
dc.subjectTracking algorithmen_US
dc.subjectSportsen_US
dc.titleSentioscope: a soccer player tracking system using model field particlesen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage1350en_US
dc.citation.epage1362en_US
dc.citation.volumeNumber26en_US
dc.citation.issueNumber7en_US
dc.identifier.doi10.1109/TCSVT.2015.2455713en_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US


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