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      Sentioscope: a soccer player tracking system using model field particles

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      Author
      Baysal, S.
      Duygulu, P.
      Date
      2016
      Source Title
      IEEE Transactions on Circuits and Systems for Video Technology
      Print ISSN
      1051-8215
      Publisher
      Institute of Electrical and Electronics Engineers
      Volume
      26
      Issue
      7
      Pages
      1350 - 1362
      Language
      English
      Type
      Article
      Item Usage Stats
      194
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      601
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      Abstract
      Tracking 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.
      Keywords
      Model field particles
      Multiple-object tracking
      Sentioscope
      Soccer player tracking
      Sports video analysis
      Motion analysis
      Motion estimation
      State space methods
      Tracking (position)
      Illumination changes
      Multiple object tracking
      Particle filter
      Sentioscope
      Soccer player
      Sports video analysis
      State - space models
      Tracking algorithm
      Sports
      Permalink
      http://hdl.handle.net/11693/36506
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/TCSVT.2015.2455713
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      • Department of Computer Engineering 1427
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