A Tennis Training Application Using 3D Gesture Recognition

  • Cristian García Bauza
  • Juan D’Amato
  • Andrés Gariglio
  • María José Abásolo
  • Marcelo Vénere
  • Cristina Manresa-Yee
  • Ramon Mas-Sansó
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7378)


This paper presents a sport training system which recognizes user movements from data of the Wiimote device with accelerometer technology. Recognizing a new gesture involves the normalization of the Wiimote data and searching in a gesture templates database. The Dynamic Time Warping (DTW) comparison algorithm is used as a correlation function to compare the new gesture with every template. Based on prior training, the system can successfully recognize different sport shots. Particularly the system is instantiated for tennis training. The user visualizes the trajectory of the ball in a three-dimensional environment and he can interact with virtual objects that follow Newton dynamics.


Gesture recognition Wiimote Videogames Sport training Tennis training Accelerometer Computer graphics Dynamic Time Warping 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bowman, D.A., Kruijff, E., LaViola, J.J., Poupyrev, I.: 3D User Interfaces: Theory and Practice. Addison Wesley Longman Publishing Co., Inc., Redwood City (2004)Google Scholar
  2. 2.
    Perrin, S., Cassinelli, A., Ishikawa, M.: Gesture recognition using laser-based tracking system. In: FGR, pp. 541–546 (2004)Google Scholar
  3. 3.
    Turk, M.: Gesture recognition. Handbook of Virtual Environments, pp. 223–238 (2001)Google Scholar
  4. 4.
    Vafadar, M., Behrad, A.: Human Hand Gesture Recognition Using Motion Orientation Histogram for Interaction of Handicapped Persons with Computer. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds.) ICISP 2008. LNCS, vol. 5099, pp. 378–385. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Caridakis, G., Karpouzis, K., Pateritsas, C., Drosopoulos, A., Stafylopatis, A., Kollias, S.: Hand trajectory-based gesture recognition using self-organizing feature maps and markov models. In: 2008 IEEE International Conference on Multimedia & Expo., ICME (2008)Google Scholar
  6. 6.
    Ruffaldi, E., Filippeschi, A., Avizzano, C.A., Bardy, B., Gopher, D., Bergamasco, M.: Feedback, Affordances and Accelerators for Training Sports in Virtual Environments. Presence, Teleoperations and virtual environments 20(1), 33–46 (2011)CrossRefGoogle Scholar
  7. 7.
    Müller, H., Schumacher, B., Blischke, K., Daugs, R.: Optimierung sportmotorischen Technik-Trainings durch computergestutzte Videosysteme. In: Perl, J. (ed.) Sport und Informatik, pp. 37–47. Hofmann, Schorndorf (1990)Google Scholar
  8. 8.
    Schorer, J.: Eine Studie zur Identifikation, den Mechanismen und Entwicklung senso-motorischer Expertise. Dissertation. Universität Heidelberg (2006)Google Scholar
  9. 9.
    Savelsbergh, G.J.P., Williams, A.M., Van der Kamp, J., Ward, P.: Visual search, anticipation and expertise in soccer goalkeepers. Journal of Sports Sciences 20, 279–287 (2002)CrossRefGoogle Scholar
  10. 10.
    Liu, X., Sun, J., He, Y., Liu, Y., Cao, L.: Overview of Virtual Reality Apply to Sports. JCIT: Journal of Convergence Information Technology 6(12), 1–7 (2011)CrossRefGoogle Scholar
  11. 11.
    Bideau, B., Kulpa, R., Vignais, N., Brault, S., Multon, F., Craig, C.: Using Virtual Reality to Analyze Sports Performance. IEEE Computer Graphics and Applications 30(2), 14–21 (2010)Google Scholar
  12. 12.
    Ruffaldi, E., Filippeschi, A., Avizzano, C.A., Bardy, B., Gopher, D., Bergamasco, M.: Feedback, Affordances and Accelerators for Training Sports in Virtual Environments. Presence, Teleoperations and virtual environments 20(1), 33–46 (2011)CrossRefGoogle Scholar
  13. 13.
    Christian, J., Krieger, H., Holzinger, A., Behringer, R.: Virtual and Mixed Reality Interfaces for e-Training: Examples of Applications in Light Aircraft Maintenance. In: Stephanidis, C. (ed.) HCI 2007, Part III. LNCS, vol. 4556, pp. 520–529. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  14. 14.
    Tanaka, K.: Virtual Training System using feedback for sport skill learning. Int. J. of Computer Science in Sport. 8(2), 1–7 (2009)Google Scholar
  15. 15.
    Siemon, A., Wegener, R., Bader, F., Hieber, T., Schmid, U.: Video Games can Improve Performance in Sports. An Empirical Study with Wii Sports Bowling. In: Wallhoff, F., Rigol, G. (Hrsg.) Proceedings of the KI 2009 Workshop on Human-Machine-Interaction (2009)Google Scholar
  16. 16.
    Chow, Y.: 3D Spatial Interaction with the Wii Remote for Head-Mounted Display Virtual Reality. World Academy of Science, Engineering and Technology 50, 377–383 (2009)Google Scholar
  17. 17.
    Leong, T., Lai, J., Panza, J., Pong, P., Hong, J.: Wii Want to Write: An Accelerometer Based Gesture Recognition System. In: International Conference on Recent and Emerging Advanced Technologies in Engineering, pp. 4–7. Carnegie Mellon University (2009)Google Scholar
  18. 18.
    Senin, P.: Dynamic time warping algorithm review. Technical Report CSDL-08-04, Department of Information and Computer Sciences. University of Hawaii, Honolulu, Hawaii 96822 (2008)Google Scholar
  19. 19.
    Niezen, G., Hancke, G.: Gesture recognition as ubiquitous input for mobile phones. In: International Workshop on Devices that Alter Perception (DAP 2008), Conjunction with Ubicomp (2008)Google Scholar
  20. 20.
    Liu, J., Wang, Z., Zhong, L., Wickramasuriya, J., Vasudevan, V.: uWave: Accelerometer based Personalized Gesture Recognition and Its Applications. In: IEEE PerCom (2009)Google Scholar
  21. 21.
    Wilson, D.H., Wilson, A.: Gesture Recognition using the XWand. Technical Report CMURI-TR-04-57. CMU Robotics Institute (2004)Google Scholar
  22. 22.
    Holt, G.A., Reinders, M.J.T., Hendriks, E.A.: Multi-Dimensional Dynamic Time Warping for Gesture Recognition. In: Thirteenth Annual Conference of the Advanced School for Computing and Imaging (2007)Google Scholar
  23. 23.
    D’amato, J.P., García Bauza, C.: Simulación de Escenarios Tridimensionales Dinámicos, Grade thesis dissertation. Universidad Nacional del Centro de la Pcia de Buenos Aires, Tandil, Argentina (2004)Google Scholar
  24. 24.
    Newton Game Dynamics - Physics Engine,
  25. 25.
    García Bauza, C., Lazo, M., Vénere, M.: Incorporación de comportamiento físico en motores gráficos. In: Mecánica Computacional, vol. XXVII, pp. 3023–3039 (2008)Google Scholar
  26. 26.

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Cristian García Bauza
    • 1
    • 2
  • Juan D’Amato
    • 1
    • 2
  • Andrés Gariglio
    • 1
  • María José Abásolo
    • 3
    • 4
  • Marcelo Vénere
    • 1
    • 5
  • Cristina Manresa-Yee
    • 6
  • Ramon Mas-Sansó
    • 6
  1. 1.Instituto PLADEMAUniversidad Nacional del Centro de la Provincia de Buenos AiresTandilArgentina
  2. 2.CONICETArgentina
  3. 3.Universidad Nacional de La PlataLa PlataArgentina
  4. 4.Comision de Investigaciones Científicas de la Provincia de Buenos AiresArgentina
  5. 5.CNEAArgentina
  6. 6.Universitat de les Illes BalearsPalmaEspaña

Personalised recommendations