Innovative Methodology of New Database Creation for 3D Face Recognition

3D image acquisition technology has become feasible and economical. Retention of geometric information of the object is the primary advantage of 3D data which represents real time scenario closely. Hence, it necessitates a good scan of 3D face of a person to enhance the 3D face recognition system performance. This study proposes a methodology that aims to develop a novel 3D face database. This work is based on the Microsoft Kinect, whose sensor is characterized by noise and outliers over a certain distance. Thus, preprocessing and segmentation phaes are necessary to detect and extract the region of interest (the face of the person). Then a 3D reconstruction surface takes place. All the simulations have been performed on the faces of people, easily acquired in our laboratory in real time. As a result, an acceptable 3D face database with different pose and variation of facial expressions was obtained.