Occlusal surface reconstruction of human teeth from a single image based on object and sensor physical characteristics

Image formation involves understanding sensor characteristics and object reflectance. In dentistry, an accurate 3-D representation of the human jaw may be used for diagnostic and treatment purposes. Photogrammetry can offer a flexible, cost effective solution for accurate 3-D representation of the human teeth, which can be used for diagnostic and treatment purposes. Nonetheless there are several challenges, such as the non-friendly image acquisition environment inside the human mouth, problems with lighting and errors due to the data acquisition sensors. In this paper, we focus on the 3D surface reconstruction aspect for human teeth based on a single image. We introduce a more realistic formulation of the shape-from-shading (SFS) problem by considering the image formation components; the camera, the light source, and the surface reflectance. We propose a non-Lambertian SFS algorithm under perspective projection which benefits from camera calibration parameters. We take into account the attenuation of illumination due to near-field imaging. The surface reflectance is modeled using Oren-Nayar-Wolff model which accounts for the retro-reflection case. Our experiments provide promising quantitative metric results for the proposed approach.