Abstract: Modeling a 3D face model that resembles a human face has been an important issue in computer graphics. A number of researchers have proposed various modeling methodologies to model the human face realistically. However, despite the fact that these methods give high-quality results, the time, cost, and labor required to generate such models by these methods are often high. In this paper, we propose a fully automatic face modeling method that can rapidly create a realistic 3D face model on the basis of a single 2D image. We studied 200 frontal facial images and captured their statistical shape variations. Using these properties, facial features were detected from the images. The depth information of the facial features was then estimated using an anthropometrical measurement database of human faces. Finally, by aligning the feature points three-dimensionally and interpolating them, a facial surface is generated. Finally, upon these 3-dimensional alignment of the facial features, a surface interpolates these feature points are created. As a result, we could obtain realistic 3D faces models of several individuals without any efforts. Further, the computational cost of our method was much lower than that of other methods. Thus, our method showed remarkably fast performance.