A Visual System for Hand Gesture Recognition in Human-Computer Interaction

  • Matti-Antero Okkonen
  • Vili Kellokumpu
  • Matti Pietikäinen
  • Janne Heikkilä
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)

Abstract

Visual hand gestures offer an interesting modality for Human-Computer-Interaction (HCI) applications. Gesture recognition and hand tracking, however, are not trivial tasks and real environments set a lot of challenges to algorithms performing such activities. In this paper, a novel combination of techniques is presented for tracking and recognition of hand gestures in real, cluttered environments. In addition to combining existing techniques, a method for locating a hand and segmenting it from an arm in binary silhouettes and a foreground model for color segmentation is proposed. A single hand is tracked with a single camera and the trajectory information is extracted along with recognition of five different gestures. This information is exploited for replacing the operations of a normal computer mouse. The silhouette of the hand is extracted as a combination of different segmentation methods: An adaptive colour model based segmentation is combined with intensity and chromaticity based background subtraction techniques to achieve robust performance in cluttered scenes. An affine-invariant Fourier-descriptor is derived from the silhouette, which is then classified to a hand shape class with support vector machines (SVM). Gestures are recognized as changes in the hand shape with a finite state machine (FSM).

Keywords

Support Vector Machine Finite State Machine Gesture Recognition Foreground Object Hand Shape 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Matti-Antero Okkonen
    • 1
  • Vili Kellokumpu
    • 1
  • Matti Pietikäinen
    • 1
  • Janne Heikkilä
    • 1
  1. 1.Department of Electrical and Information Engineering, P.O. Box 4500, FI-90014, University of OuluFinland

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