By Topic

Clustering Method Evaluation for Hidden Markov Model Based Real-Time Gesture Recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Prasad, J.S. ; Robot. & AI Lab., Indian Inst. of Inf. Technol., Allahabad, India ; Nandi, G.C.

This paper deals with the development of high performance real-time system for complex dynamic gesture recognition. The various motion features are extracted from the video frames which are used by HMM classifier. We used several clustering techniques for performance evaluation of the classifier. Our system vectorises gestures into sequential symbols both for training and testing. We found very encouraging results and the proposed method has potential application in the field of human machine interaction.

Published in:

Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on

Date of Conference:

27-28 Oct. 2009