This paper presents a new method for detecting semantic events which may happen in a soccer game. Our method requires the position information of the players and ball as input, which can be provided by a tracking system from processing either microwave signals or video sequences. Based on the tracking data, the method detects a wide range of player actions and game events using a set of heuristic rules which are derived from a hierarchical entity-relationship model representing the prior knowledge of soccer events. We have applied the proposed method as a key enabling module in a realworld sports entertainment application and the experimental results are given in the paper.
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Tovinkere et al. (2001) studied this question.
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