Automatic eyes and nose detection using curvature analysis

Abstract

In the present work we propose a method for detecting the nose and eyes position when we observe a scene that contains a face. The main goal of the proposed technique is that it capable of bypassing the 3D explicit mapping of the face and instead take advantage of the information available in the Depth gradient map of the face. To this end we will introduce a simple false positive rejection approach restricting the distance between the eyes, and between the eyes and the nose. The main idea is to use nose candidates to estimate those regions where is expected to find the eyes, and vice versa. Experiments with Texas database are presented and the proposed approach is testes when data presents different power of noise and when faces are in different positions with respect to the camera.