AUTOMATED 3D–2D PROJECTIVE REGISTRATION OF HUMAN FACIAL IMAGES USING EDGE FEATURES

Abstract

In this paper, we describe a method of automatic 3D–2D projective registration between the 3D (i.e. polygonal face surface derived from CT or MRI data) and the 2D faces of the same individual in the photographs. Our task is to make a realistic 3D model face for post-surgical simulation by pasting color textures accurately on the face surface. We utilize edge features such as external edge (facial outline) and internal edges like eye, nose and mouth edges from both the 3D face and photographs for matching. We define 3D edge as a set of 3D surface points which is 2D edge on the projected space. We choose 3D edges within the specific regions alone by automatically categorizing the 3D face into eye, nose, mouth and ear regions using a knowledge-based technique. Experimentally we have shown that for human face matching selected region-based edge yields better matching accuracy than that of the usual edge. Moreover, we average the root mean square (RMS) measures of the selected facial regions rather than computing a single RMS measure to obtain matching uniformity over the entire region.