PCA-Based 3D Face Photography

This paper presents a 3D face photography system based on a small set of training facial range images. The training set is composed by 2D texture and 3D range images (i.e. geometry) of a single subject with different facial expressions. The basic idea behind the method is to create texture and geometry spaces based on the training set and transformations to go from one space to the other. The main goal of the proposed approach is to obtain a geometry representation of a given face provided as a texture image, which undergoes a series of transformations through the texture and geometry spaces. Facial feature points are obtained by an active shape model (ASM) extracted from the 2D gray-level images. PCA then is used to represent the face dataset, thus defining an orthonormal basis of texture and range data. An input face is given by a gray-level face image to which the ASM is matched. The extracted ASM is fed to the PCA basis representation and a 3D version of the 2D input image is bui...

• Type: Conference
• Year: 2008
• Where: SIBGRAPI
• Authors: Jesus P. Mena-Chalco, Ives Macedo, Luiz Velho, Roberto Marcondes Cesar Junior
• Keywords: Computer Graphics, Geometry Spaces, Range Images, SIBGRAPI 2008, Training Set