An Efficient Ball and Player Detection in Broadcast Tennis Video

  • M. Archana
  • M. Kalaiselvi Geetha
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 384)


Ball and player detection in Broadcast Tennis Video (BTV) is a critical and challenging task in tennis video semantic analysis. Informally, the challenges are due to the camera motion and the other causes such as the small size of the tennis ball and many objects resembles the ball and considering the player, the human body along with the tennis racket is not detected completely. In this paper, it is proposed an improved object detection technique in BTV. In order to detect the ball, logical AND operation is applied between the created background and image difference is performed, from that ball candidates are detected by applying threshold values and dilated. Player detection is performed from AND results by finding the biggest blob and filling the whole detected object by removing the small one. The experimental result shows that the proposed approach achieved the higher accuracy in object identification, their object the landing frames and positions. It is achieved a high hit rate and less fail rate.


Tennis ball detection Player detection Background subtraction Broadcast tennis video Hit rate Fail rate 


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  1. 1.
    Lai, J.-H., Chien, S.-Y.: Semantic scalability using tennis videos as examples. Multimedia Tools and Applications 59(2), 585–599 (2012)CrossRefGoogle Scholar
  2. 2.
    Cross, R.: The footprint of a tennis ball. Sports Engineering 17(4), 239–247 (2014)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Yu, X., Sim, C.-H., Wang, J.R., Cheong, L.F.: A trajectory-based ball detection and tracking algorithm in broadcast tennis video. In: Image Processing, International Conference on ICIP 2004, vol. 2, pp. 1049–1052 (2004)Google Scholar
  4. 4.
    Furht, B., Greenberg, J., Westwater, R.: Motion estimation algorithms for video compression. Springer Science and Business Media, vol. 379 (2012)Google Scholar
  5. 5.
    Cross, R.: Impact of sports balls with striking implements. Sports Engineering 17(1), 3–22 (2014)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Yan, F., Christmas, W., Kittler, J.: Ball Tracking for Tennis Video Annotation. Springer International Publishing In Computer Vision in Sports (2014)Google Scholar
  7. 7.
    Aggarwal, J.K., Ryoo, M.S.: Human activity analysis: A review. ACM Computing Surveys (CSUR) 43(3), 16 (2011)CrossRefGoogle Scholar
  8. 8.
    Chen, H.-T., Chou, C.-L., Fu, T.-S., Lee, S.-Y., Lin, B.-S.P.: Recognizing tactic patterns in broadcast basketball video using player trajectory. Journal of Visual Communication and Image Representation 23(6), 932–947 (2012)CrossRefGoogle Scholar
  9. 9.
    Martn, R., Martnez, J.M.: Automatic Players Detection and Tracking in Multi-camera Tennis Videos. Springer International Publishing In Human Behavior Understanding in Networked Sensing, pp. 191–209 (2014)Google Scholar
  10. 10.
    Wang, Y., Han, Y., Zhang, D.: Research on Detection and Tracking of Player in Broadcast Sports Video. International Journal of Multimedia and Ubiquitous Engineering 9(11), 1–10 (2014)MATHGoogle Scholar
  11. 11.
    Yan, F., Christmas, W., Kittler, J.: Ball Tracking for Tennis Video Annotation. Springer International Publishing In Computer Vision in Sports, pp. 25–45 (2014)Google Scholar
  12. 12.
    Sakurai, S., Reid, M., Elliott, B.: Ball spin in the tennis serve: spin rate and axis of rotation. Sports Biomechanics 12(1), 23–29 (2013)CrossRefGoogle Scholar
  13. 13.
    Nicolaides, A., Elliott, N., Kelley, J., Pinaffo, M., Allen, T.: Effect of string bed pattern on ball spin generation from a tennis racket. Sports Engineering 16(3), 181–188 (2013)CrossRefGoogle Scholar
  14. 14.
    Choppin, S.: An investigation into the power point in tennis. Sports Engineering 16(3), 173–180 (2013)CrossRefGoogle Scholar
  15. 15.
    Choppin, S., Goodwill, S., Haake, S.: Impact characteristics of the ball and racket during play at the Wimbledon qualifying tournament. Sports Engineering 13(4), 163–170 (2011)CrossRefGoogle Scholar
  16. 16.
    Spurr, J., Goodwill, S., Kelley, J., Haake, S.: Measuring the inertial properties of a tennis racket. Procedia Engineering 72, 569–574 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAnnamalai UniversityAnnamalai NagarIndia

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