Low resolution face recognition based on support vector data description

Sang-Woong Lee, Jooyoung Park, Seong-Whan Lee

Abstract: In the face recognition process, it is important to deal with a facial image of low-resolution. For low-resolution face recognition, we propose a new method of extending the SVDD, which is one of the most well-known support vector learning methods for the one-class problem. The proposed method can recognize a person even with a low-resolution image.