Self-calibration Based 3D Information Extraction and Application in Broadcast Soccer Video (original) (raw)

Abstract

This paper proposes a new method based on self-calibration to estimate the ball’s 3D position in broadcast soccer video. According to the physical limitation, the ball’s 3D position is estimated through the camera position and the ball’s virtual shadow, which is the point of intersection between the playfield and the line through the camera’s optical center and the ball. First, the virtual shadow is computed by the homography between playfield and image plane. For the image having enough corresponding points, the map is determined directly; for those images not having enough these points, their homographies are estimated through global motion estimation. Then, based on self-calibrating for rotating and zooming camera, and the homography, the camera’s position in the playfield is estimated. Experiments show that the proposed method can extract ball’s 3D position information without referring to other object with assuming height and obtain promising results.

This work is partly supported by NEC Research China and “Science 100 Plan” of Chinese Academy of Sciences.

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References

  1. Yu, X., Hay, T.S., Leong, H.W.: 3D Reconstruction and enrichment of broadcast soccer video. In: Proc. ACM Multimedia, New York, NY, USA (October 2004)
    Google Scholar
  2. Bebie, T., Bieri, H.: Reconstructing soccer game from video sequence. In: Proc. of ICIP 1998, pp. 898–902 (1998)
    Google Scholar
  3. Bebie, T., Bieri, H.: A Video-Based 3D-econstruction of Soccer games. In: EuroGraphics 2000 (2000)
    Google Scholar
  4. Reid, I., North, A.: 3D trajectories from a single viewpoint using shadows. British Machine Vision Conference, 863–872 (1998)
    Google Scholar
  5. Ohno, Y., Miura, J., Shirai, Y.: Tracking players and estimation of the 3D position of a ball in soccer games. In: The International Conference on Pattern Recognition, pp. 145–148 (2000)
    Google Scholar
  6. Yamada, A., Shirai, Y., Miura, J.: Tracking players and a ball in video image sequence and estimating camera parameters for 3D interpretation of soccer games. In: The International Conference on Pattern Recognition, pp. 303–306 (2002)
    Google Scholar
  7. Ancona, N., Cicirelli, G., Stella, E., Ditante, A.: Ball detection in static images with support vector machines for classification. Image and Vision Computing 21, 675–692 (2003)
    Article Google Scholar
  8. D’Orazio, T., Guaragnella, C., Leo, M., Distante, A.: A new algorithm for ball recognition using circle Hough transform and neural classifier. Pattern Recognition 37, 393–408 (2004)
    Article Google Scholar
  9. Ren, C., Orwell, J., Jones, G.A., Xu, M.: A general framework for 3D soccer ball estimation and tracking. In: Proc. IEEE International Conference on Image Processing (2004)
    Google Scholar
  10. Xu, M., Orwell, J., Jones, G.: Tracking football players with multiple cameras. In: Proc. IEEE International Conference on Image Processing (2004)
    Google Scholar
  11. Iwase, S., Saito, H.: Parallel Tracking of All Soccer Players by Integrating Detected Positions in Multiple View Images. In: Proc. International Conference on Pattern Recognition (2004)
    Google Scholar
  12. Saito, H., Inamoto, N., Iwase, S.: Sports scene analysis and visualization from multiple-view video. In: Porc. IEEE International Conference on Multimedia & Expo (2004)
    Google Scholar
  13. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge
    Google Scholar
  14. Yu, X., Xu, C., Leong, H.W., Tian, Q., Tang, Q., Wan, K.W.: Trajectory-Based Ball Detection and Tracking with Applications to Semantic Analysis of Broadcast Soccer Video. In: Proc. ACM Multimedia 2003, Berkeley, CA, USA, November 2003, pp. 11–20 (2003)
    Google Scholar
  15. Yu, X., Tian, Q., Wan, K.W.: A Novel Ball Detection Framework for Real Soccer Video. In: Proc. ICME 2003, 6-9 July, vol. 2, pp. 265–268 (2003)
    Google Scholar
  16. Tong, X., Lu, H., Liu, Q.: An Effective and Fast Soccer Ball Detection and Tracking Method. In: Proc. ICPR 2004, August 23-26, vol. 4, pp. 795–798 (2004)
    Google Scholar
  17. Kim, H., Hong, K.S.: Robust image mosaicing of soccer videos using self-calibration and line tracking. Pattern Analysis & Applications 4, 9–19 (2001)
    Article MATH MathSciNet Google Scholar
  18. Kim, T., Seo, Y., Hong, K.S.: Physics-based 3D position analysis of a soccer ball from monocular image sequence. In: The International Conference on Computer Vision, pp. 721–726 (1998)
    Google Scholar
  19. FIFA, Laws of the game, http://www.fifa.com/en/regulations/regulation/0,1584,3,00.html
  20. Zhang, Z.: Flexible camera calibration by viewing a plane from unknown orientations, Computer Vision. In: The Proceedings of the Seventh IEEE International Conference on Computer Vision, 20-27 September, vol. 1, pp. 666–673 (1999)
    Google Scholar
  21. Seo, Y., Hong, K.S.: Auto-calibration of a rotating and zooming camera. In: Proceedings of the IAPR workshop on Machine vision applications, pp. 274–277 (1998)
    Google Scholar
  22. Agapito, L., Hayman, E., Reid, I.: Self-Calibration of Rotating and Zooming Cameras. International Journal of Computer Vision 45(2), 107–127 (2001)
    Article MATH Google Scholar
  23. Liang, D., Liu, Y., Huang, Q., Gao, W.: A Scheme for Ball Detection and Tracking in Broadcast Soccer Video. In: Pacific-Rim Conference on Multimedia (2005) (accepted)
    Google Scholar

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, 150001, Harbin, China
    Yang Liu, Dawei Liang & Wen Gao
  2. Graduate School, Chinese Academy of Sciences, 100039, Beijing, China
    Qingming Huang & Wen Gao

Authors

  1. Yang Liu
  2. Dawei Liang
  3. Qingming Huang
  4. Wen Gao

Editor information

Editors and Affiliations

  1. Center for Visual Information Technology, International Institute of Information Technology, Hyderabad, India
    P. J. Narayanan
  2. Department of Computer Science, Columbia University, 500 West 120th Street, NY 10027, New York, USA
    Shree K. Nayar
  3. Microsoft Research Asia, P.O. Box, Beijing, P.R. China
    Heung-Yeung Shum

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© 2006 Springer-Verlag Berlin Heidelberg

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Liu, Y., Liang, D., Huang, Q., Gao, W. (2006). Self-calibration Based 3D Information Extraction and Application in Broadcast Soccer Video. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3852. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612704\_85

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