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2010
IEEE

Motion Fields to Predict Play Evolution in Dynamic Sport Scenes

11 years 10 months ago
Motion Fields to Predict Play Evolution in Dynamic Sport Scenes
Videos of multi-player team sports provide a challenging domain for dynamic scene analysis. Player actions and interactions are complex as they are driven by many factors, such as the short-term goals of the individual player, the overall team strategy, the rules of the sport, and the current context of the game. We show that constrained multi-agent events can be analyzed and even predicted from video. Such analysis requires estimating the global movements of all players in the scene at any time, and is needed for modeling and predicting how the multi-agent play evolves over time on the field. To this end, we propose a novel approach to detect the locations of where the play evolution will proceed, e.g. where interesting events will occur, by tracking player positions and movements over time. We start by extracting the ground level sparse movement of players in each time-step, and then generate a dense motion field. Using this field we detect locations where the motion converges, i...
Kihwan Kim, Matthias Grundmann, Ariel Shamir, Iain
Added 17 Jul 2010
Updated 17 Jul 2010
Type Conference
Year 2010
Where CVPR
Authors Kihwan Kim, Matthias Grundmann, Ariel Shamir, Iain Matthews, Jessica Hodgins, Irfan Essa
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