TY  - CONF
AU  - Bogdan Raducanu
AU  - Fadi Dornaika
A2  - WACV
PY  - 2012//
TI  - Appearance-based Face Recognition Using A Supervised Manifold Learning Framework
BT  - IEEE Workshop on the Applications of Computer Vision
SP  - 465
EP  - 470
PB  - IEEE Xplore
N2  - Many natural image sets, depicting objects whose appearance is changing due to motion, pose or light variations, can be considered samples of a low-dimension nonlinear manifold embedded in the high-dimensional observation space (the space of all possible images). The main contribution of our work is represented by a Supervised Laplacian Eigemaps (S-LE) algorithm, which exploits the class label information for mapping the original data in the embedded space. Our proposed approach benefits from two important properties: i) it is discriminative, and ii) it adaptively selects the neighbors of a sample without using any predefined neighborhood size. Experiments were conducted on four face databases and the results demonstrate that the proposed algorithm significantly outperforms many linear and non-linear embedding techniques. Although we've focused on the face recognition problem, the proposed approach could also be extended to other category of objects characterized by large variance in their appearance.
SN  - 1550-5790
SN  - 978-1-4673-0233-3
L1  - http://refbase.cvc.uab.es/files/RaD2012d.pdf
UR  - http://dx.doi.org/10.1109/WACV.2012.6163045
N1  - OR;MV
ID  - Bogdan Raducanu2012
ER  -