Recognizing Hand Gestures of a Dancer

  • Divya Hariharan
  • Tinku Acharya
  • Sushmita Mitra
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6744)

Abstract

A new and simple two-level decision making system has been designed for performing scale-, translation- and rotation-invariant recognition of various single-hand gestures of a dancer. The orientation filter is used at the first-level to generate a feature vector that is able to distinguish between several gestures. At the second-level the silhouette of the different gestures is extracted, followed by the generation of the corresponding skeleton and the evaluation of the gradients at its end points. These gradients constitute the second feature set, for recognizing those gestures which remain to be identified at the first-level. An application has been provided in the domain of single-hand gestures of Bharatanatyam, an Indian classical dance form.

Keywords

Gesture recognition feature extraction skeleton matching orientation histogram 

References

  1. 1.
    Acharya, T., Ray, A.K.: Image Processing Principles and Applications. John Wiley, New Jersey (2005)CrossRefGoogle Scholar
  2. 2.
    Freeman, W.T., Roth, M.: Orientation histograms for hand gesture recognition. In: Proceedings of IEEE International Workshop on Automatic Face and Gesture Recognition, pp. 296–301. IEEE, Los Alamitos (1994)Google Scholar
  3. 3.
    Verma, M.: Bharatanatyam: Origin, Styles and Techniques, chap, pp. 295–315. Abhishek Publishers, Hastas (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Divya Hariharan
    • 1
  • Tinku Acharya
    • 2
  • Sushmita Mitra
    • 1
  1. 1.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia
  2. 2.Videonetics Technology Private LimitedKolkataIndia

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