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Various 3-D face synthesis techniques have been proposed and extensively used in many applications. Compared with others, single view-based face synthesis technology allows unsupervised 3-D face reconstruction without any offline operations. Although many algorithms have been published, automatic and robust single view-based 3-D face synthesis still remains unsolved. In contrast to other methods, the single view-based 3-D face synthesis algorithm conducted in this paper enables automated 3-D face synthesis from an arbitrary head-and-shoulder image with the complex background. The developed system first detects the face using Bayesian skin-tone classification based on only the chrominance component, Cr. Based on the detected face, a few salient facial features, such as the corners of the eyebrows and contours of the eyes, mouth, and chin are in turn extracted using variant algorithms, including a dynamic chin extraction mechanism that will be detailed in this paper. Then, face model adaptation consisting of both global and local adaptations is imposed, according to geometric information provided by the extracted facial features. Finally, the 3-D specific face is synthesized using the adapted 3-D face model with a texture map directly derived from the input face image, followed by the implementation of facial animation using this synthesized face.