Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
9-2009
Abstract
Based on moving least square, a multi-view ear pose interpolation and corresponding recognition approach is proposed. This work firstly analyzes the shape characteristics of actual trace caused by ear pose varying in feature space. Then according to training samples pose projection, we manage to recover the complete multi-view ear pose manifold by using moving least square pose interpolation. The constructed multi-view ear pose manifolds can be easily utilized to recognize ear images captured under different views based on finding the minimal projection distance to the manifolds. The experimental results and some comparisons show the new method is superior to manifold learning method and B-Spline based recognition method.
Keywords
Face recognition, move less square, small sample size problem, move less square approximation, Gauss weight function
Discipline
Artificial Intelligence and Robotics
Research Areas
Information Systems and Management
Publication
Emerging Intelligent Computing Technology and Applications: 5th International Conference, ICIC 2009, Ulsan, South Korea, September 16-19: Proceedings
Volume
5755
First Page
1085
Last Page
1097
ISBN
9783642040191
Identifier
10.1007/978-3-642-04020-7_116
Publisher
Springer
City or Country
Cham
Citation
LIU, Heng; ZHANG, David; and ZHANG, Zhiyuan.
Multi-view ear recognition based on moving least square pose interpolation. (2009). Emerging Intelligent Computing Technology and Applications: 5th International Conference, ICIC 2009, Ulsan, South Korea, September 16-19: Proceedings. 5755, 1085-1097.
Available at: https://ink.library.smu.edu.sg/sis_research/7937
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/978-3-642-04020-7_116