Exploring of alternative representations of facial images for face recognition

Description and classification of face images is a significant task of computer vision, machine learning and pattern recognition communities. In the past, researchers have made tremendous efforts in this task. Previous researchers always seek high-resolution face images for better image classification. However, with this paper, we present and demonstrate a new opinion that in some cases the use of alternative representations of facial images are very useful for face recognition and properly reducing the image resolution might be beneficial to better classification of face images. This may be attributed to the deformable property of faces and the fact that the proposed alternative representations can in some extent reduce the within-class difference of facial images. Also, the presented idea appear to be useful for helping people to improve face recognition techniques in real worlds.