Real Time Hand Gesture Recognition Including Hand Segmentation and Tracking

  • Thomas Coogan
  • George Awad
  • Junwei Han
  • Alistair Sutherland
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4291)


In this paper we present a system that performs automatic gesture recognition. The system consists of two main components: (i) A unified technique for segmentation and tracking of face and hands using a skin detection algorithm along with handling occlusion between skin objects to keep track of the status of the occluded parts. This is realized by combining 3 useful features, namely, color, motion and position. (ii) A static and dynamic gesture recognition system. Static gesture recognition is achieved using a robust hand shape classification, based on PCA subspaces, that is invariant to scale along with small translation and rotation transformations. Combining hand shape classification with position information and using DHMMs allows us to accomplish dynamic gesture recognition.


Gesture Recognition Search Window Hand Shape Hand Gesture Recognition Occlusion Status 
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 2006

Authors and Affiliations

  • Thomas Coogan
    • 1
  • George Awad
    • 1
  • Junwei Han
    • 1
  • Alistair Sutherland
    • 1
  1. 1.Dublin City UniversityIreland

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