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.
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References
Ekin, A., Teklap, A.M.: Shot Type Classification by Dominant Color for Sports Video Segmentation and Summarization. In: International Conference on Acoustics, Speech and Signal Processing, vol. 3, pp. 173–176 (2003)
Ekin, A., Teklap, A.M., Mehrotra, R.: Automatic Soccer Video Analysis and Summarization. IEEE Transactions on Image Processing 12(7), 796–807 (2003)
Yang, Y.-Q., Lu, Y.-D., Chen, W.: A framework for automatic detection of soccer goal event based on cinematic template. In: Proc. Int. Conf. on Machine Learning and Cybernetics, vol. 6, pp. 26–29 (2004)
Zhou, W., Vellaikal, A., Kuo, C.J.: Rule-based Video Classification System for Basketball Video Indexing. ACM Multimedia (2000)
Babaguchi, N., Kawai, Y., Ogura, T., Kitahashi, T.: Personalized abstraction of broadcasted American football video by highlight selection. Multimedia, IEEE Transactions 6(4), 575–586 (2004)
Tjondronegoro, D.W., Chen, Y.-P.P., Pham, B.: Classification of self-consumable highlights for soccer video summaries. In: IEEE International Conference on Multimedia and Expo., vol. 127-30, pp. 579–582 (2004)
Leonardi, R., Migliorati, P., Prandini, M.: Semantic indexing of soccer audio-visual sequences: a multimodal approach based on controlled Markov chains. Circuits and Systems for Video Technology, IEEE Transactions 14(5), 634–643 (2004)
Yusoff, Y., Christmas, W., Kittler, J.: Video Shot Cut Detection Using Adaptive Thresholding. In: British Machine Vision Conference, pp. 362–372 (2000)
Bescos, J., Menendez, J.M., Cisneros, G., Cabrera, J., Martinez, J.M.: A Unified Approach to Gradual Shot Transition Detection. In: Proc. Int. Conf. on Image Processing, vol. 3, pp. 949–952 (2000)
Wolf, C., Jolion, J.-M., Chassaing, F.: Text Localization, Enhancement and Binarization in Multimedia Document. In: 16th International Conference on Pattern Recognition, vol. 2, pp. 11–15 (2002)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE TRansactions on Systems, Man and Cybernetics 9, 62–66 (1979)
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© 2005 Springer-Verlag Berlin Heidelberg
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Kim, EJ., Lee, GG., Jung, C., Kim, SK., Kim, JY., Kim, WY. (2005). A Video Summarization Method for Basketball Game. In: Ho, YS., Kim, H.J. (eds) Advances in Multimedia Information Processing - PCM 2005. PCM 2005. Lecture Notes in Computer Science, vol 3767. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11581772_67
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DOI: https://doi.org/10.1007/11581772_67
Publisher Name: Springer, Berlin, Heidelberg
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