Automated Offside Detection by Spatio-Temporal Analysis of Football Videos
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In this paper, we propose a new automated method to detect offsides from football match videos. The advantage of our method is that it can strictly follow the official offside rules in which the dynamics of play actions are spatio-temporally investigated. Furthermore, to overcome the difficult task of tracking the two-dimensional locations of the players and the ball, we utilized geometric characteristics on the perspective projection coupled with a Kalman filter to estimate information necessary for offside detection. Based on these methods, our prototype system can recognize whether an attacking player who crossed the offside line receives a pass from their teammate or not. To the best of our knowledge, our proposed method is the first method that can automatically determine offsides from video. Furthermore, this method is designed to enable online processing in the future.
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