A novel approach to hand-gesture recognition in a human-robot dialog system

Pujan Ziaie, Thomas Müller, Alois Knoll

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

In this paper, a reliable, fast and robust approach for static hand gesture recognition in the domain of a Human-Robot interaction system is presented. The method is based on computing the likelihood of different existing gesture-types and assigning a probability to every type by using Bayesian inference rules. For this purpose, two classes of geometrical invariants has been defined and the gesture likelihoods of both of the invariant-classes are estimated by means of a modified K-Nearest Neighbors classifier. One of the invariant-classes consists of the well-known Hu moments and the other one encompasses five defined geometrical attributes that are transformation, rotation and scale invariant, which are obtained from the outer-contour of a hand. Given the experimental results of this approach in the domain of the Joint-Action Science and Technology (JAST) project, it appears to have a very considerable performance of more than 95% correct classification results on average for three types of gestures (pointing, grasping and holding-out) under various lighting conditions and hand poses.

Original languageEnglish
Title of host publication2008 1st International Workshops on Image Processing Theory, Tools and Applications, IPTA 2008
DOIs
StatePublished - 2008
Event2008 1st International Workshops on Image Processing Theory, Tools and Applications, IPTA 2008 - Sousse, Tunisia
Duration: 23 Nov 200826 Nov 2008

Publication series

Name2008 1st International Workshops on Image Processing Theory, Tools and Applications, IPTA 2008

Conference

Conference2008 1st International Workshops on Image Processing Theory, Tools and Applications, IPTA 2008
Country/TerritoryTunisia
CitySousse
Period23/11/0826/11/08

Keywords

  • Bayes theory
  • Gesture recognition
  • Hu moments
  • Image processing
  • K-nearest-neighbors

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