Facial Modeling from an Uncalibrated face Image Using a Coarse-to-fine Genetic Algorithm

Abstract

This paper presents a genetic algorithm-based optimization approach for facial modeling form an uncelebrated face image using a flexible generic parameterized facial model (FGPFM). The FPGFM 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 randomly yawed face bused on the projection transformation. The facial modeling problem is formulated as a parameter optimization problem and the objective function is also given. Moreover, a course-to-fin 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, experimental results with texture mapping demonstrate the effectiveness of the proposed method.