Detection of tennis court lines for sport video categorization
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
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Objects like field lines and players are important for semantic analysis in soccer video. In this paper, we propose effective methods for field lines and players detection and recognition. Regions of field lines and players are first segmented from shot of wide angle view. Gray value top-hat transform is then performed on the segmented region to detect field lines. Mid-lines, end-lines and penalty-lines are then recognized based on their positions. Template matching method is adopted to detect and recognize players. Four types of templates for players are matched on the segmented region. Accurate position of player can be obtained after template matching, and the type of player is also identified. Experiment results on various data-sets with different production styles show effectiveness of our method.