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Multi-camera video surveillance for real-time analysis and reconstruction of soccer games

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Abstract

Soccer analysis and reconstruction is one of the most interesting challenges for wide-area video surveillance applications. Techniques and system implementation for tracking the ball and players with multiple stationary cameras are discussed. With video data captured from a football stadium, the real-world, real-time positions of the ball and players can be generated. The whole system contains a two-stage workflow, i.e., single view and multi-view processing. The first stage includes categorizing of players and filtering of the ball after changing detection against an adaptive background and image-plane tracking. Occlusion reasoning and tracking-back is applied for robust ball filtering. In the multi-view stage, multiple observations from overlapped single views are fused to refine players’ positions and to estimate 3-D ball positions using geometric constraints. Experimental results on real data from long sequences are demonstrated.

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Authors and Affiliations

  1. School of Informatics, University of Bradford, Bradford, UK

    Jinchang Ren

  2. School of Computers, Northwestern Polytechnic University, Xi’an, China

    Jinchang Ren

  3. Xi’an Jiaotong Liverpool University, Suzhou, China

    Ming Xu

  4. Digital Imaging Research Centre, Kingston University, Kingston upon Thames, UK

    James Orwell & Graeme A. Jones

Authors
  1. Jinchang Ren
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  2. Ming Xu
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  3. James Orwell
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  4. Graeme A. Jones
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Correspondence to Jinchang Ren.

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Ren, J., Xu, M., Orwell, J. et al. Multi-camera video surveillance for real-time analysis and reconstruction of soccer games. Machine Vision and Applications 21, 855–863 (2010). https://doi.org/10.1007/s00138-009-0212-0

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  • DOI: https://doi.org/10.1007/s00138-009-0212-0

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