Statistically deformable face models for cranio-facial reconstruction

Abstract

Forensic facial reconstruction aims at estimating the facial outlook associated to an unknown skull specimen. Estimation is based on tabulated average values of soft tissue thicknesses measured at a sparse set of landmarks on the skull. Traditional 'plastic' methods apply modeling clay or plasticine on a cast of the skull approximating the estimated tissue depths at the landmarks and interpolating in between. Current computerized techniques mimic this landmark interpolation procedure using a single facial surface template. However, the resulting reconstruction is biased by the specific choice of the template. We reduce this bias by using a flexible statistical model of a dense set of facial surface points combined with an associated sparse set of skull landmarks. The reconstruction is obtained by fitting the model skull landmarks to the corresponding landmarks indicated on a digital copy of the skull to be reconstructed. The fitting process alternates between changing the face-specific statistical model parameters and interpolating the remaining landmark fit error using a minimal bending thin-plate spline (TPS) based deformation. This iterative process is shown by experiment to converge to a realistic reconstruction of the face, independent of the initial template.