Human Hand Gesture Recognition Using Motion Orientation Histogram for Interaction of Handicapped Persons with Computer

  • Maryam Vafadar
  • Alireza Behrad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5099)

Abstract

Some groups of handicapped persons cannot reliably move the mouse and do the necessary operation on it to control the computer. However they can do some 3-d hand motions. Variety of tools has been presented for these users to interact with computer. Hand gesture recognition is one of the proper methods for this purpose. This paper presents a new algorithm for hand gesture recognition. In this algorithm, after constructing motion history image of video frames for each gesture and applying necessary processing on this image, motion orientation histogram vector is extracted. These vectors are then used for the training of Hidden Markov Model and hand gesture recognition. We tested the proposed algorithm with different hand gestures and results showed the correct gesture recognition rate of 90 percent. Comparing the results of proposed method with those of other methods showed that in addition to eliminating traditional problems in this area, recognition rate has been improved up to 4 percent.

Keywords

Hand gesture recognition Motion history image Hidden Markov model Motion orientation histogram 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Maryam Vafadar
    • 1
  • Alireza Behrad
    • 1
  1. 1.Faculty of EngineeringShahed UniversityTehranIran

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