A novel approach for dynamic hand gesture recognition using contour-based similarity images

Abstract

A novel approach is proposed for the recognition of moving hand gestures based on the representation of hand motions as contour-based similarity images (CBSIs). The CBSI was constructed by calculating the similarity between hand contours in different frames. The input CBSI was then matched with CBSIs in the database to recognize the hand gesture. The proposed continuous hand gesture recognition algorithm can simultaneously divide the continuous gestures into disjointed gestures and recognize them. No restrictive assumptions were considered for the motion of the hand between the disjointed gestures. The proposed algorithm was tested using hand gestures from American Sign Language and the results showed a recognition rate of 91.3% for disjointed gestures and 90.4% for continuous gestures. The experimental results illustrate the efficiency of the algorithm for noisy videos.

Keywords:

• hand gesture recognition
• scale-invariant feature transform
• contour-based similarity image
• American Sign Language

2010 AMS Subject Classifications::

• 68T45
• 62H35
• 68T10

Acknowledgements

The authors would like to thank the editor and reviewers for their valuable and constructive comments and suggestions to improve the quality of the paper.