Hand detection and pose estimation

Hand detection and pose estimation for creating human-computer interaction project is supported by the Polish Ministry of Science and Higher Education under research grant no. IP2011 023071 from the Science Budget 2012-2013. The project involves the following computer vision tasks:


  1. J. Nalepa and M. Kawulok, “Fast and accurate hand shape classification,” in Beyond Databases Architectures and Structures, CCIS. Springer Berlin Heidelberg, 2014, in press.
  2. J. Nalepa and M. Kawulok, “Parallel hand shape classification,” in Proc. IEEE ISM, 2013, pp. 401-402.
  3. M. Kawulok, J. Kawulok, and J. Nalepa, “Spatial-based skin detection using discriminative skin-presence features,” Pattern Recogn. Lett., vol. 41, pp. 3-13, 2014.
  4. M. Kawulok, J. Nalepa, and J. Kawulok, “Skin detection and segmentation in color images,” in Advances in Low-Level Color Image Processing, M. E. Celebi and B. Smolka, Eds., vol. 11 of Lecture Notes in Computational Vision and Biomechanics, pp. 329-366. Springer Netherlands, 2014.
  5. J. Nalepa, T. Grzejszczak, and M. Kawulok, “Wrist localization in color images for hand gesture recognition,” in Proc. Int. Conf. on Man-Machine Interaction, ICMMI 2013. 2014, vol. 242 of Advances in Intelligent and Soft Computing, pp. 79-86, Springer.
  6. M. Kawulok, J. Kawulok, J. Nalepa, and M. Papiez, “Skin detection using spatial analysis with adaptive seed,” in Proc. IEEE Int. Conf. on Image Processing (ICIP 2013), 2013, pp. 3720-3724.
  7. M. Kawulok, “Fast propagation-based skin regions segmentation in color images,” in Proc. IEEE FG, 2013, pp. 1-7.
  8. T. Grzejszczak, J. Nalepa, and M. Kawulok, “Real-time wrist localization in hand silhouettes,” in Computer Recognition Systems, CORES 2013, R. Burduk, M. Kurzynski, M. Wozniak, and A. Zolnierek, Eds. 2013, vol. 226 of Advances in Intelligent and Soft Computing, pp. 439-449, Springer.
  9. M. Kawulok and J. Nalepa, “Support vector machines training data selection using a genetic algorithm,” in Statistical Techniques in Pattern Recognition, S+SSPR 2012, vol. 7626 of LNCS, pp. 557-565, Springer-Verlag Berlin Heidelberg, 2012.
  10. M. Kawulok, “Skin detection using color and distance transform,” in Proc. ICCVG. 2012, vol. 7594 of LNCS, pp. 449-456, Springer-Verlag Berlin Heidelberg.
  11. T. Grzejszczak, M. Mikulski, T. Szkodny, and K. Jedrasiak, “Gesture based robot control,” in Int. Conf. on Computer Vision and Graphics, ICCVG 2012. 2012, vol. 7594 of LNCS, pp. 407-413, Springer-Verlag Berlin Heidelberg.
  12. M. Czupryna and M. Kawulok, “Real-time vision pointer interface,” in Proc. Int. Symp. ELMAR 2012, 2012, pp. 49-52.
  13. M. Kawulok, “Texture analysis for skin probability maps refinement,” in Proc. MCPR, vol. 7329 of LNCS, pp. 75-84, Springer-Verlag Berlin Heidelberg, 2012.
  14. G. Koszowski and M. Kawulok, “Virtual hand modeling for gesture recognition,” Studia Informatica, vol. 33, no. 2B, pp. 35-36, 2012.

Hand gesture database

The project involved creation of a database for hand gesture recognition (HGR), which is published and described here.

Michal Kawulok, D.Sc.
e-mail: michal.kawulok@polsl.pl

Silesian University of Technology
Institute of Informatics
Akademicka 16, room 504, 44-100 Gliwice, Poland