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

摘要

This paper presents a genetic algorithm-based optimization approach for facial modeling from an uncalibrated face image using a flexible generic parameterized facial model (FGPFM). The FGPFM can be easily modified using the facial features as parameters of FGPFM to construct an accurate specific 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-fine approach based on our intelligent genetic algorithm which can efficiently 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 effectiveness of the proposed method.