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 and no face-specific regularization is present. We reduce the 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 statistical model also provides a probability value, which can be used to regularize the reconstruction towards more plausible outlooks. 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. Furthermore, estimated properties of the skull specimen (BMI, age and gender e.g.) can be incorporated as conditions on the reconstruction by removing property-related shape variation from the statistical model description before the fitting process. This iterative statistical model-based reconstruction process is shown by experiment to converge to a realistic reconstruction of the face, independent of the initial template.

Bayesian estimation of optimal craniofacial reconstructions

“…The proposed CFR technique in this paper is an extension and refinement of our previous work reported in [42][43][44]. In order to eliminate the template-related model bias and to minimize the unrealistic character of the reconstructions caused by large generic model deformations, we propose a refined statistical CFM for reconstruction.…”

Computerized craniofacial reconstruction: Conceptual framework and review

“…Something similar is done by [6], but instead of growing tissue, they model the muscles onto the skull after which the facial features and skin are added. In the early work of Claes et al [18,26,[31][32][33][34] a sparse set of anatomical landmarks indicated manually on the skull is used as well, but no thickness values are set out. Instead soft-tissue thickness are incorporated into the craniofacial model instead of the skull representation in order to exploit the influence of tissue thickness on facial geometry and vice versa.…”

Augmentation of linear facial anthropometrics through modern morphometrics: a facial convexity example

“…The crucial disadvantage of PCA for studying a specific variation of interest was the inability to control the type of variation extracted by each PC. A solution to this problem was found 19 using a property pathway which is the trajectory through the face-space defining the covariance in facial form with the variance in any given property. 20 In other words, a property pathway is the combination of PCs that cumulatively expresses the direction of variation caused by any property of interest.…”