Automatic Video Editing: Original Tracking Method Applied to Basketball Players in Video Sequences

  • Colin Le Nost
  • Florent LefevreEmail author
  • Vincent Bombardier
  • Patrick Charpentier
  • Nicolas Krommenacker
  • Bertrand Petat
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10884)


The main task here is to track several basketball players during a game and to be able to retrieve their whole trajectories at the end. The final application is to get some statistics about each players and to identify some special events like free throw or to determine when a counterattack is going to happen. The originality of the solution states in the way the tracking is performed: instead of studying the close environment of each player, all the players are detected on each frame then we are using specific informations like background, speed vector, color or distance between players to link player’s positions and create the whole trajectories. We will compare our results with a benchmark of algorithms to see that our solution is quite efficient in term of tracking and speed.


Automatic editing Tracking Sports analysis 


  1. 1.
    Games recorded in 2016 from BCMess, a Luxembourg Basketball club.
  2. 2.
    Grabner, H., Grabner, M., Bischof, H.: Real-time tracking via on-line boosting. In: BMVC, vol. 6 (2006)Google Scholar
  3. 3.
    Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: Exploiting the circulant structure of tracking-by-detection with kernels. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7575, pp. 702–715. Springer, Heidelberg (2012). Scholar
  4. 4.
    Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: High-speed tracking with kernelized correlation filters. TPAMI 37(3), 583–596 (2015)CrossRefGoogle Scholar
  5. 5.
    Kalal, Z., Mikolajczyk, K., Matas, J.: Forward-backward error: automatic detection of tracking failures. In: 2010 20th International Conference on Pattern Recognition (ICPR), pp. 2756–2759. IEEE (2010)Google Scholar
  6. 6.
    Babenko, B., Yang, M.-H., Belongie, S.: Visual tracking with online multiple instance learning. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 983–990 (2009)Google Scholar
  7. 7.
    Kalal, Z., Mikolajczyk, K., Matas, J.: Tracking-learning-detection. IEEE Pattern Anal. Mach. Intell. 34(7), 1409–1422 (2012)CrossRefGoogle Scholar
  8. 8.
    Janku, P., Koplik, K., Dulik, T., Szabo, I.: Comparison of tracking algorithms implemented in OpenCV. In: MATEC Web of Conferences, vol. 76, p. 04031 (2016)CrossRefGoogle Scholar
  9. 9.
    Suzuki, S., Abe, K.: Topological structural analysis of digitized binary images by border following. Comput. Vis. Graph. Image Process. 30(1), 32–46 (1985)CrossRefGoogle Scholar
  10. 10.
    ISO 11664–4: 1976 L* A* B* Colour Space. Joint ISO/CIE Standard, ISO. ISO 11664–4 (2008)Google Scholar
  11. 11.
    Zeng, Z., Jia, J., Yu, D., Chen, Y., Zhu, Z.: Pixel modeling using histograms based on fuzzy partitions for dynamic background subtraction. IEEE Trans. Fuzzy Syst. 25, 584–593 (2017)CrossRefGoogle Scholar
  12. 12.
    Hayet, J.B., Mathes, T., Czyz, J., Piater, J., Verly, J., Macq, B.: A modular multi-camera framework for team sports tracking. In: IEEE Conference on Advanced Video and Signal Based Surveillance (2005)Google Scholar
  13. 13.
    Du, W., Hayet, J.B., Piater, J., Verly, J.: Collaborative multi-camera tracking of athletes in team sports. In: Workshop on Computer Vision Based Analysis in Sport, Environments, pp. 2–13 (2006)Google Scholar
  14. 14.
    KaewTraKulPong, P., Bowden, R.: An improved adaptive background mixture model for real-time tracking with shadow detection. In: Remagnino, P., Jones, G.A., Paragios, N., Regazzoni, C.S. (eds.) Video-Based Surveillance Systems, pp. 135–144. Springer, Boston (2002). Scholar
  15. 15.
    Davis, J., Goadrich, M.: The relationship between precision-recall and ROC curves. In: 23rd International Conference on Machine Learning, vol. 6, pp. 233–240 (2006)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Colin Le Nost
    • 1
  • Florent Lefevre
    • 2
    • 3
    Email author
  • Vincent Bombardier
    • 2
  • Patrick Charpentier
    • 2
  • Nicolas Krommenacker
    • 2
  • Bertrand Petat
    • 3
  1. 1.Ecole Nationale Supérieure des Mines de NancyNancyFrance
  2. 2.Université de Lorraine, CNRS, CRANNancyFrance
  3. 3.CitizenCamMaxévilleFrance

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