A Novel Approach for 3D Head Segmentation and Facial Feature Points Extraction

This work presents a novel approach for 3D head segmentation as well as for extraction of facial features vertices. These tasks are the preliminary task for retrieval, recognition, classification and tracking processes. 3D head regions are detected from a cloud of points using the ratio of geodesic to Euclidean distances between pairs of vertices that combine neighbor coordinates and position information of the point. In this paper, we propose a new algorithm to extract automatically feature points inside the facial region based on the topology of 3D face. Furthermore, in order to validate our approach, we have run experimentations on several types of full 3D head that differ in number of points and surfaces, gender and ethnic. Also, to approve its robustness, we apply our approach on a benchmark of scanned faces containing 67 models.