Pitching-shot is known to be a root-shot for subsequent baseball video content analysis, e.g., event or highlight detection, and video structure parsing. In this paper, we integrate multiple feature analysis and fuzzy classification techniques to achieve pitching-shot detection in commercial baseball video. The adopted features include color (e.g., field color percentage and dominant color), temporal motion, and spatial activity distribution. On the other hand, domain knowledge of the baseball game forms the basis for fuzzy inference rules. Experiment results show that our detection rate is capable of achieving 95.76%. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Lie, W. N., Lin, G. S., & Cheng, S. L. (2006). Pitching shot detection based on multiple feature analysis and fuzzy classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4261 LNCS, pp. 852–860). Springer Verlag. https://doi.org/10.1007/11922162_97
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