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Hand Posture Recognition Using Real-Time Artificial Evolution

  • Benoit Kaufmann
  • Jean Louchet
  • Evelyne Lutton
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6024)

Abstract

In this paper, we present a hand posture recognition system (configuration and position) we designed as part of a gestural man-machine interface. After a simple image preprocessing, the parameter space (corresponding to the configuration and spatial position of the user’s hand) is directly explored using a population of points evolved via an Evolution Strategy. Giving the priority to exploring the parameter space rather than the image, is an alternative to the classical generalisation of the Hough Transform and allows to meet the real-time constraints of the project. The application is an Augmented Reality prototype for a long term exhibition at the Cité des Sciences, Paris. As it will be open to the general public, rather than using conventional peripherals like a mouse or a joystick, a more natural interface has been chosen, using a microcamera embedded into virtual reality goggles in order to exploit the images of the user’s hand as input data and enable the user to manipulate virtual objects without any specific training.

Keywords

Video Sequence Input Image Augmented Reality Virtual Object Hough Transform 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Benoit Kaufmann
    • 1
  • Jean Louchet
    • 2
  • Evelyne Lutton
    • 1
  1. 1.INRIA SaclayParc Orsay UniversitéOrsay Cedex
  2. 2.ARTENIAChatillon

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