Geometry-Based Skin Colour Estimation For Bare Torso Surface Reconstruction

Three-dimensional imaging techniques have been endeavouring at reaching affordable ubiquity. Nevertheless, its use in clinical practice can be hampered by less than naturally looking surfaces that greatly impact its visual inspection. This work considers the task of surface reconstruction from point clouds of non-rigid scenes acquired through structured-light-based methods, wherein the reconstructed surface contains some level of imperfection to be inpainted before visualized by experts in a clinically oriented context. Appertain to the topic, the recovery of colour information for missing or damaged partial regions is considered. A local geometry-based interpolation method is proposed for the reconstruction of the bare human torso and compared against a reference differential equations based inpainting method. Widely used perceptual distance-based metrics, such as PSNR, SSIM and MS-SSIM, and the evaluation from a panel of experienced breast cancer surgeons is presented for the discussion on inpainting quality assessment.