Facial modeling from an uncalibrated face image using a coarse-to-fine genetic algorithm

This paper presents a genetic algorithm-based optimization approach for facial modeling from an uncalibrated face image using a #exible generic parameterized facial model (FGPFM). The FGPFM can be easily modi"ed using the facial features as parameters of FGPFM to construct an accurate speci"c 3D facial model from only a photograph of an individual with a yawed face based on the projection transformation. The facial modeling problem is formulated as a parameter optimization problem and the objective function is also given. Moreover, a coarse-to-"ne approach based on our intelligent genetic algorithm which can e$ciently solve the large parameter optimization problems is used to accelerate the search for an optimal solution. Furthermore, sensitivity analysis and experimental results with texture mapping demonstrate the e!ectiveness of the proposed method. ( 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.