By Topic

3D Face Recognition by Surface Classification Image and PCA

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

5 Author(s)
Lei Yunqi ; Dept. of Comput. Sci., Xiamen Univ., Xiamen, China ; Chen Dongjie ; Yuan Meiling ; Li Qingmin
more authors

An approach of 3D face recognition by using of facial surface classification image and PCA is presented. In the step of pre-processing, the scattered 3D points of a facial surface are normalized by surface fitting algorithm using multilevel B-splines approximation. Then, partial-ICP method is utilized to adjust 3D face model to be in the right front pose for a better recognition performance. By using the normalized facial depth image been acquired through the two previous steps, and by calculating the Gaussian and mean curvatures at each point, the surface types are classified and the classification result is used to mark different kinds of area on the facial depth image by 8 gray-levels. This achieved gray image is named as Surface Classification Image (SCI) and the SCI now represents the 3D features of the face and then it is input to the process of PCA to obtain the SCI eigenfaces to recognize the face. In the experiments conducted on 3D Facial database ZJU-3DFED of Zhejiang University, we obtained the rank-1 identification score of 94.5%, which outperformed the result of using PCA method directly on the face depth image (instead of SCI) by 16.5%.

Published in:

Machine Vision, 2009. ICMV '09. Second International Conference on

Date of Conference:

28-30 Dec. 2009