|
|
|
| Kernel Uncorrelated Space Algorithm and Its Application to Face Recognition |
| Lin Yu-e; Gu Guo-chang;Liu Hai-bo; Shen Jing |
| College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China |
|
|
|
|
Abstract Uncorrelated space algorithm is a fast method for the uncorrelated discriminant vectors extraction，but it may encounter the small size samples problem when it is applied to face recognition task. In addition, it is only a linear feature extraction technique. In this paper，kernel uncorrelated space algorithm is proposed. The key of the proposed algorithm is to how to compute the uncorrelated space in the higher dimensional feature space. As to this problem, a very simple and easy method is proposed, which originates from the eigenface that transforms the computation of the high order matrix into the computation of the low order matrix, and then the actual computation of the uncorrelated space in the higher dimensional feature space is reduced to a standard eignenvalue problem. In addition, the proposed algorithm can effectively overcome small size samples problem. The numerical experiments on facial databases of ORL show that the proposed method is effective and feasible.
|
|
Received: 02 June 2008
|
|
|
|
|
|
|
|
|
2009, Vol. 31 
