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

3D head tracking and pose-robust 2D texture map-based face recognition using a simple ellipsoid model

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)
Kwang Ho An ; Electr. Eng. & Comput. Sci. Dept., Korea Adv. Inst. of Sci. & Technol., Daejeon ; Myung Jin Chung

A human face provides a variety of different communicative functions such as identification, the perception of emotional expression, and lip-reading. For these reasons, many applications in robotics require tracking and recognizing a human face. A novel face recognition system should be able to deal with various changes in face images, such as pose, illumination, and expression, among which pose variation is the most difficult one to deal with. Therefore, face registration (alignment) is the key of robust face recognition. If we can register face images into frontal views, the recognition task would be much easier. To align a face image into a canonical frontal view, we need to know the pose information of a human head. Therefore, in this paper, we propose a novel method for modeling a human head as a simple 3D ellipsoid. And also, we present 3D head tracking and pose estimation methods using the proposed ellipsoidal model. After recovering full motion of the head, we can register face images with pose variations into stabilized view images which are suitable for frontal face recognition. By doing so, simple and efficient frontal face recognition can be easily carried out in the stabilized texture map space instead of the original input image space. To evaluate the feasibility of the proposed approach using a simple ellipsoid model, 3D head tracking experiments are carried out on 45 image sequences with ground truth from Boston University, and several face recognition experiments are conducted on our laboratory database and the Yale Face Database B by using subspace-based face recognition methods such as PCA, PCA+LAD, and DCV.

Published in:

Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on

Date of Conference:

22-26 Sept. 2008

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.