Research On3D Face Based On Morphable Model

With the development of hardware technology of photograph,3D technology has been widelyused in the field of movie, games, and medical care and other fields. Compared with2D image,3Dimage enjoys more space information and has closely lined to people’s daily life. In recent years,research based on3D face model has become a hot issue in computer vision and graphic, which playsan important role in3D face animation and recognition.3D face model generally have four methods, parameter model, muscle model, the vision modeland the morphable model. Morphable model when compared to the other method has the advantagesof good quality and automation, is supposed to be the most successful method in3D face model.However, it is still difficult to establish Morphable model in a3D face database. Many predecessorshad put forward the methods like ICP, NICP, time method, etc. But they have limitations in facealignment accuracy and the accuracy of established correspondence. This paper focuses on theconstruction and application of3D face Morphable model. The main contents of the present paperinclude:1. The construction of3D face morphable model. We study various methods of constructing3Dface morphable model on the basis of a large-scale3D face database and analyze their advantages anddisadvantages. The experimental result shows that the standard3D surface deformation methods havegood effect in face alignment accuracy and the accuracy of correspondences. And then, according tothe characteristics of the database, we modify the strategy in searching local correspondences, whichnot only improve the accuracy of correspondences, but also speed up the process of energy functionoptimization. As the deformation of face belongs to non-rigid transformation, we present our iterativedense3D face alignment method on the basis of standard3D surface deformation method, which referto the frame of non-rigid algorithms.2. The evaluation of3D face morphable model. Measures of alignment quality have to be domainspecific. We compare our method with the traditional surface deformation method from four aspects.The results show that our method is superior to traditional one in the alignment accuracy and theaccuracy of correspondence.3.3D face reconstruction based on a single face image. According to only one face image3Dface reconstruction is an ill-problem. However, since the3D morhpable model has lots of prioriknowledge,3D face shape can be estimated by this face model. Because of the complexity ofmorphable model parameters, the sparse3D face morphable model is choosen to reconstruct the3D face shape by means of fitting the feature points between the3D face model and the face image. Andthen,3D face shape is projected to image to generate the face texture. According to the experimentalresult, the reconstruction3D face shape is smooth and the texture is realistic.