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This paper proposes a model-based approach for 3D facial shape recovery using a small set of feature points from an input image of unknown pose and illumination. Previous model-based approaches usually require both texture (shading) and shape information from the input image in order to perform 3D facial shape recovery. However, the methods discussed here need only the 2D feature points from a single input image to reconstruct the 3D shape. Experimental results show acceptable reconstructed shapes when compared to the ground truth and previous approaches. This work has potential value in applications such face recognition at-a distance (FRAD), where the classical shape-from-X (e.g., stereo, motion and shading) algorithms are not feasible due to input image quality.