Player localization using multiple static cameras for sports visualization

We present a novel approach for robust localization of multiple people observed using multiple cameras. We use this location information to generate sports visualizations, which include displaying a virtual offside line in soccer games, and showing players' positions and motion patterns. Our ma...

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Published in2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition pp. 731 - 738
Main Authors Hamid, R, Kumar, R K, Grundmann, M, Kihwan Kim, Essa, I, Hodgins, J
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2010
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ISBN1424469848
9781424469840
ISSN1063-6919
1063-6919
DOI10.1109/CVPR.2010.5540142

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Abstract We present a novel approach for robust localization of multiple people observed using multiple cameras. We use this location information to generate sports visualizations, which include displaying a virtual offside line in soccer games, and showing players' positions and motion patterns. Our main contribution is the modeling and analysis for the problem of fusing corresponding players' positional information as finding minimum weight K-length cycles in complete K-partite graphs. To this end, we use a dynamic programming based approach that varies over a continuum of being maximally to minimally greedy in terms of the number of paths explored at each iteration. We present an end-to-end sports visualization framework that employs our proposed algorithm-class. We demonstrate the robustness of our framework by testing it on 60,000 frames of soccer footage captured over 5 different illumination conditions, play types, and team attire.
AbstractList We present a novel approach for robust localization of multiple people observed using multiple cameras. We use this location information to generate sports visualizations, which include displaying a virtual offside line in soccer games, and showing players' positions and motion patterns. Our main contribution is the modeling and analysis for the problem of fusing corresponding players' positional information as finding minimum weight K-length cycles in complete K-partite graphs. To this end, we use a dynamic programming based approach that varies over a continuum of being maximally to minimally greedy in terms of the number of paths explored at each iteration. We present an end-to-end sports visualization framework that employs our proposed algorithm-class. We demonstrate the robustness of our framework by testing it on 60,000 frames of soccer footage captured over 5 different illumination conditions, play types, and team attire.
Author Kihwan Kim
Hamid, R
Hodgins, J
Essa, I
Grundmann, M
Kumar, R K
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  organization: Disney Res., Pittsburgh, PA, USA
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Snippet We present a novel approach for robust localization of multiple people observed using multiple cameras. We use this location information to generate sports...
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StartPage 731
SubjectTerms Cameras
Visualization
Title Player localization using multiple static cameras for sports visualization
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