Advertisement

Multiscale Detection of Gesture Patterns in Continuous Motion Trajectories

  • Radu-Daniel Vatavu
  • Laurent Grisoni
  • Stefan-Gheorghe Pentiuc
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5934)

Abstract

We describe a numerical method for scale invariant detection of gesture patterns in continuous 2D motions. The algorithm is fast due to our rejection-based reasoning achieved using a new set of curvature-based functions which we call Integral Absolute Curvatures. Detection rates above 96% are reported on a large data set consisting of 72,000 samples with demonstrated low execution time. The technique can be used to automatically detect gesture patterns in unconstrained motions in order to enable click-free interactions.

Keywords

gesture recognition pattern detection multiscale curvature integral of curvature motion trajectory 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Arvo, J., Novins, K.: Fluid Sketches: Continuous Recognition and Morphing of Simple Hand-Drawn Shapes. In: ACM UIST 2000, pp. 73–80 (2000)Google Scholar
  2. 2.
    Arvo, J., Novins, K.: Fluid Sketching of Directed Graphs. In: 7th Australasian User Interface Conference, pp. 81–86. Australian Computer Society (2006)Google Scholar
  3. 3.
    Do Carmo, M.: Differential Geometry of Curves and Surfaces. Prentice-Hall, Englewood Cliffs (1976)zbMATHGoogle Scholar
  4. 4.
    Cerlinca, T.I., Pentiuc, S.G., Vatavu, R.D., Cerlinca, M.C.: Hand posture recognition for human-robot interaction. In: WMISI at ICMI 2007, pp. 47–50 (2007)Google Scholar
  5. 5.
    Dong, Q., Wu, Y., Hu, Z.: Gesture Segmentation from a Video Sequence Using Greedy Similarity Measure. In: ICPR 2006, pp. 331–334 (2006)Google Scholar
  6. 6.
    Hershberger, J., Snoeyink, J.: Speeding Up the Douglas-Peucker Line-Simplification Algorithm. In: Proc. of 5th Symposium on Data Handling, pp. 134–143 (1992)Google Scholar
  7. 7.
    LaViola, J.J.: Sketching and gestures 101. In: ACM SIGGRAPH 2007 Courses, p. 2. ACM, New York (2007)Google Scholar
  8. 8.
    Marcel, S.: Hand Posture Recognition in a Body-Face centered space. In: ACM CHI 1999 Extended Abstracts, pp. 302–303. ACM Press, New York (1999)CrossRefGoogle Scholar
  9. 9.
    Moeslund, T.B., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Computer Vision and Image Understanding 104(2), 90–126 (2006)CrossRefGoogle Scholar
  10. 10.
    Pavlovic, V.I., Sharma, R., Huang, T.S.: Visual interpretation of hand gestures for human–computer interaction: A review. IEEE TPAMI 19(7), 677–695 (1997)Google Scholar
  11. 11.
    Poppe, R.: Vision-based human motion analysis: An overview. Computer Vision and Image Understanding 108(1-2), 4–18 (2007)CrossRefGoogle Scholar
  12. 12.
    Reng, L., Moeslund, T.B., Granum, E.: Finding Motion Primitives in Human Body Gestures. In: Gibet, S., Courty, N., Kamp, J.-F. (eds.) GW 2005. LNCS (LNAI), vol. 3881, pp. 133–144. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Rubine, D.: Specifying gestures by example. In: Proc. of SIGGRAPH 1991, pp. 329–337. ACM Press, New York (1991)CrossRefGoogle Scholar
  14. 14.
    Sowa, T.: The Recognition and Comprehension of Hand Gestures - A Review and Research Agenda. In: Wachsmuth, I., Knoblich, G. (eds.) ZiF Research Group International Workshop. LNCS (LNAI), vol. 4930, pp. 38–56. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Schlomer, T., Poppinga, B., Henze, N., Boll, S.: Gesture Recognition with a Wii Controller. In: TEI 2008, Bonn, Germany, pp. 11–14 (2008)Google Scholar
  16. 16.
    Thorne, M., Burke, D., van de Panne, M.: Motion doodles: an interface for sketching character motion. In: ACM SIGGRAPH 2004, pp. 424–431 (2004)Google Scholar
  17. 17.
    Vatavu, R.D., Grisoni, L., Pentiuc, S.G.: Gesture Recognition based on Elastic Deformation Energies. In: Sales Dias, M., Gibet, S., Wanderley, M.M., Bastos, R. (eds.) GW 2007. LNCS (LNAI), vol. 5085, pp. 1–12. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  18. 18.
    Vatavu, R.D., Pentiuc, S.G.: Interactive Coffee Tables: Interfacing TV within an Intuitive, Fun and Shared Experience. In: Tscheligi, M., Obrist, M., Lugmayr, A. (eds.) EuroITV 2008. LNCS, vol. 5066, pp. 183–187. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  19. 19.
    Wilson, A.D.: Robust computer vision-based detection of pinching for one and two-handed gesture input. In: ACM UIST 2006, pp. 255–258 (2006)Google Scholar
  20. 20.
    Wobbrock, J.O., Wilson, A.D., Li, Y.: Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes. In: UIST 2007, pp. 159–168 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Radu-Daniel Vatavu
    • 1
  • Laurent Grisoni
    • 2
  • Stefan-Gheorghe Pentiuc
    • 1
  1. 1.University Stefan cel Mare of SuceavaRomania
  2. 2.Laboratoire d’Informatique Fondamentale de LilleFrance

Personalised recommendations