Abstract
There have been various research efforts on automatic summarization of sports video. However, most previous works were based on event detection and thus cannot reflect the semantic importance of scenes and content of a game. In this paper, a summarization method for basketball video is presented. The proposed method keeps track of score changes of the game by reading the numbers on the score board. Analysis of the score variation yields a video summary that consists of semantically important and interesting scenes such as reversal or pursuit. Experimental results indicate that the proposed method can summarize basketball video with reasonable accuracy. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Kim, E. J., Lee, G. G., Jung, C., Kim, S. K., Kim, J. Y., & Kim, W. Y. (2005). A video summarization method for basketball game. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3767 LNCS, pp. 765–775). Springer Verlag. https://doi.org/10.1007/11581772_67
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