Visual similarity issues in face recognition

The paper discusses several issues of visual similarity in face detection and recognition. Using a straightforward concept of keypoint correspondences, a method is proposed to formalise the subjective impressions of |similar faces|, |similar eyes|, |similar chins|, etc. The method exploits the mechanism of affine near-duplicate fragment detection originally proposed for visual information retrieval. It is shown that using such a method, a simple and relatively reliable face detection/identification systems can be build without any model (or training) of human faces, which can work with images containing multiple faces shown on random backgrounds. Additionally, it is proposed how the same approach can be used to optimise databases of face images and to identify individuals who are at higher risks of mistaken face identification.