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

3D Face Recognition Based on 3D Ridge Lines in Range Data

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)
Mahoor, M.H. ; Miami Univ., Coral Gables ; Abdel-Mottaleb, M.

In this paper we present an approach for 3D face recognition from range data based on the principal curvature, kmax, and Hausdorff distance. We use the principal curvature, kmax, to represent the face image as a 3D binary image called ridge image. The ridge image shows the locations of the ridge lines around the important facial regions on the face (i.e. the eyes, the nose, and the mouth). We utilize Hausdorff distance to match the ridge image of a given probe to the created ridge images of the subjects in the gallery. For pose alignment, we extract the locations of three feature points, the inner corners of the two eyes and the tip of the nose using Gaussian curvature. These three feature points plus an auxiliary point in the center of the triangle, made by averaging the coordinates of the three feature points, are used for initial 3D face alignment. In the face recognition stage, we find the optimum pose alignment between the probe image and the gallery, which gives the minimum Hasusdorff distance between the two sets of features. This approach is used for identification of both neutral faces and faces with smile expression. Experiments on a public face database of 61 subjects resulted in 93.5% ranked one recognition rate for neutral expression and 82.0% for the faces with smile expression.

Published in:

Image Processing, 2007. ICIP 2007. IEEE International Conference on  (Volume:1 )

Date of Conference:

Sept. 16 2007-Oct. 19 2007

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.