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Soccer Formation Classification Based on Fisher Weight Map and Gaussian Mixture Models

  • Conference paper
Large-Scale Knowledge Resources. Construction and Application (LKR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4938))

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Abstract

This paper proposes a method that analyzes player formations in order to classify kick and throw-in events in soccer matches. Formations are described in terms of local head counts and mean velocities, which are converted into canonical variates using a Fisher weight map in order to select effective variates for discriminating between events. The map is acquired by supervised learning. The distribution of the variates for each event class is modeled by Gaussian mixtures in order to handle its multimodality in canonical space. Our experiments showed that the Fisher weight map extracted semantically explicable variates related to such situations as players at corners and left/right separation. Our experiments also showed that characteristically formed events, such as kick-offs and corner-kicks, were successfully classified by the Gaussian mixture models. The effect of spatial nonlinearity and fuzziness of local head counts are also evaluated.

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References

  1. Nitanda, N., Haseyama, M., Kitajima, H.: Audio Signal Segmentation and Classification Using Fuzzy Clustering (in Japanese). IEICE Trans. D-II J88-D-II(2), 302–312 (2005)

    Google Scholar 

  2. Sano, M., et al.: Automatic Real-Time Selection and Annotation of Highlight Scenes in Televised Soccer. IEICE Trans. Information and Systems E90-D(1), 224–232 (2007)

    Article  Google Scholar 

  3. Ekin, A., Tekalp, A.M., Mehrotra, R.: Automatic Soccer Video Analysis and Summarization. IEEE Trans. Image Process. 12(7), 796–807 (2003)

    Article  Google Scholar 

  4. Matsumoto, K., et al.: Optimized Camera Viewpoint Determination System for Soccer Game Broadcasting. In: Proc. MVA 2000, pp. 115–118 (2000)

    Google Scholar 

  5. Figueroa, P.J., Leite, N.J., Barros, R.M.L.: Tracking Soccer Players Aiming their Kinematical Motion Analysis. Computer Vision and Image Understanding 101(2), 122–135 (2006)

    Article  Google Scholar 

  6. Snoek, C.G.M., Worring, M.: A Review on Multimodal Video Indexing. In: Proc. ICME 2002, vol. 2, pp. 21–24 (2002)

    Google Scholar 

  7. Misu, T., et al.: Real-Time Event Detection Based on Formation Analysis of Soccer Scenes (in Japanese). In: Information Technology Letters (FIT2005), vol. 4 LI-003, pp. 141–144 (2005)

    Google Scholar 

  8. Nagase, T., Ozawa, S.: Determining Play in Soccer Scenes Using Multiple View Images (in Japanese). The Journal of the Institute of Image Information and Television Engineers 60(10), 1664–1671 (2006)

    Google Scholar 

  9. Misu, T., et al.: Visualization of Offside Lines Based on Realtime Video Processing (in Japanese). IEICE Trans. J88-D-II(8), 1681–1692 (2005)

    Google Scholar 

  10. Shinohara, Y., Otsu, N.: Facial Expression Recognition Using Fisher Weight Maps. In: Proc. IEEE 6th Intl. Conf. on Automatic Face and Gesture Recognition (FG 2004), pp. 499–504 (2004)

    Google Scholar 

  11. Ohno, Y., Miura, J., Shirai, Y.: Tracking Players and a Ball in Soccer Games. In: Proc. Int. Conf. on Multisensor Fusion and Integration for Intelligent systems, pp. 147–152 (1999)

    Google Scholar 

  12. Misu, T., et al.: Distributed Particle Filtering for Multiocular Soccer-Ball Tracking. In: Proc. ICASSP 2007, vol. 3, pp. 937–940 (2007)

    Google Scholar 

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Takenobu Tokunaga Antonio Ortega

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© 2008 Springer-Verlag Berlin Heidelberg

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Misu, T., Naemura, M., Fujii, M., Yagi, N. (2008). Soccer Formation Classification Based on Fisher Weight Map and Gaussian Mixture Models. In: Tokunaga, T., Ortega, A. (eds) Large-Scale Knowledge Resources. Construction and Application. LKR 2008. Lecture Notes in Computer Science(), vol 4938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78159-2_19

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  • DOI: https://doi.org/10.1007/978-3-540-78159-2_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78158-5

  • Online ISBN: 978-3-540-78159-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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