Hand Tracking with an Extended Self-Organizing Map

  • Andreea State
  • Foti Coleca
  • Erhardt Barth
  • Thomas Martinetz
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 198)


We introduce an extension of the self-organizing map for performing 3D hand skeleton tracking. We use a range camera for data acquisition and apply a SOM-like learning process within each frame in order to capture the hand pose. Our method uses a topology consisting of 1D and 2D segments for an improved representation of the hand. The proposed algorithm is very efficient and produces good tracking results.


hand skeleton tracking self-organizing maps kinect 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    ElKoura, G., Singh, K.: Handrix: Animating the Human Hand. In: Proc. SCA, pp. 110–119 (2003)Google Scholar
  2. 2.
    Haker, M., Böhme, M., Martinetz, T., Barth, E.: Deictic Gestures with a Time-of-Flight Camera. In: Kopp, S., Wachsmuth, I. (eds.) GW 2009. LNCS, vol. 5934, pp. 110–121. Springer, Heidelberg (2010)Google Scholar
  3. 3.
    Kohonen, T.: Self-Organizing Maps. Springer, Berlin (1995)Google Scholar
  4. 4.
    Rehg, J., Kanade, T.: Visual Tracking of High DOF Articulated Structures: An Application to Human Hand Tracking. In: Eklundh, J.-O. (ed.) ECCV 1994. LNCS, vol. 801, pp. 35–46. Springer, Heidelberg (1994)Google Scholar
  5. 5.
    Segen, J., Kumar, S.: Shadow Gestures: 3D Hand Pose Estimation using a Single Camera. In: Proceedings of Conference on Computer Vision and Pattern Recognition (1999)Google Scholar
  6. 6.
    Rosales, R., Athitsos, V., Sclaroff, S.: 3D hand pose reconstruction using specialized mappings. In: Proc. International Conference on Computer Vision, vol. 1, pp. 378–385 (2001)Google Scholar
  7. 7.
    Athitsos, V., Sclaroff, S.: Estimating 3D hand pose from a cluttered image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2003)Google Scholar
  8. 8.
    Stenger, B., Thayananthan, A., Torr, P.H.S., Cipolla, R.: Hand Pose Estimation Using Hierarchical Detection. In: Proc. International Workshop Human-Computer Interaction, pp. 105–116 (2004)Google Scholar
  9. 9.
    Bray, M., Koller-Meier, E., Gool, L.V.: Smart particle filtering for 3D hand tracking. In: Sixth IEEE International Conference on Automatic Face and Gesture Recognition, p. 675. IEEE Computer Society, Los Alamitos (2004)Google Scholar
  10. 10.
    Haker, M., Böhme, M., Martinetz, T., Barth, E.: Self-Organizing Maps for Pose Estimation with a Time-of-Flight Camera. In: Kolb, A., Koch, R. (eds.) Dyn3D 2009. LNCS, vol. 5742, pp. 142–153. Springer, Heidelberg (2009)Google Scholar
  11. 11.
    Ehlers, K., Timm, F., Barth, E., Martinetz, T.: A generalization of k-means for real time hand skeleton tracking (in preparation)Google Scholar
  12. 12.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Andreea State
    • 1
    • 2
  • Foti Coleca
    • 1
    • 3
  • Erhardt Barth
    • 1
    • 3
  • Thomas Martinetz
    • 1
  1. 1.Institute for Neuro- and BioinformaticsUniversity of LübeckLübeckGermany
  2. 2.University ”POLITEHNICA” of BucureştiBucureştiRomania
  3. 3.Gestigon GmbH, Innovations Campus LübeckLübeckGermany

Personalised recommendations