Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
1-2011
Abstract
One critical challenge encountered by existing face recognition techniques lies in the difficulties of handling varying poses. In this paper, we propose a novel pose invariant 3D face recognition scheme to improve regular face recognition from two aspects. Firstly, we propose an effective geometry based alignment approach, which transforms a 3D face mesh model to a well-aligned 2D image. Secondly, we propose to represent the facial images by a Locality Preserving Sparse Coding (LPSC) algorithm, which is more effective than the regular sparse coding algorithm for face representation. We conducted a set of extensive experiments on both 2D and 3D face recognition, in which the encouraging results showed that the proposed scheme is more effective than the regular face recognition solutions
Discipline
Computer Sciences | Databases and Information Systems
Publication
Advances in Multimedia Modeling: 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part I
Volume
6523
First Page
217
Last Page
228
ISBN
9783642178313
Identifier
10.1007/978-3-642-17832-0_21
Publisher
Springer Verlag
City or Country
Berlin
Citation
WANG, Dayong; HOI, Steven C. H.; and HE, Ying.
An Effective Approach to Pose Invariant 3D Face Recognition. (2011). Advances in Multimedia Modeling: 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part I. 6523, 217-228.
Available at: https://ink.library.smu.edu.sg/sis_research/2357
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1007/978-3-642-17832-0_21