Cart (Loading....) | Create Account
Close category search window
 

ISVM for Face 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

3 Author(s)
Sisodia, D. ; I.T Dept., S.A.T.I., Vidisha, India ; Shrivastava, S.K. ; Jain, R.C.

The similarity of human faces, unpredictable variations and aging are the crucial obstacles in face recognition. To handle this if large set of training images are used then computational complexity will get increase as images are rather high dimension but if training set kept small, performance decreases. Since both classification and feature information are necessary for a recognition system DCT is used to lower the computational complexity and SVM for classification. Since SVM is a popular classification tool but the main disadvantage of SVM is its large memory requirement and computation time to deal with large data set. Therefore we have used incremental learning approach i.e. ISVM to avoid large training time and memory consumption for face recognition. The biggest advantage of using the proposed technique is that it not only decreases the training time and updating time but also improves the classification accuracy rate up to 100%. Experiments are performed on ORL face database and results has proved that not only the training time used by the ISVM is very less compared to SVM but also the recognition rate raised to 100%. Obtained results have presented accurate face recognition system using the proposed approach..

Published in:

Computational Intelligence and Communication Networks (CICN), 2010 International Conference on

Date of Conference:

26-28 Nov. 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.