This paper describes a prototype system for surgical planning and prediction of human facial shape after craniofacial and maxillofacial surgery for patients with facial deformities. For this purpose it combines, unifies, and extends various methods from geometric modeling, finite element analysis, and image processing to render highly realistic 3D images of the post surgical situation. The basic concept of the system is to join advanced geometric modeling and animation systems such as Alias with a special purpose finite element model of the human face developed under AVS. In contrast to existing facial models we acquire facial surface and soft tissue data both from photogrammetric and CT scans of the individual. After initial data preprocessing, reconstruction, and registration, a finite element model of the facial surface and soft tissue is provided which is based on triangular finite elements. Stiffness parameters of the soft tissue are computed using segmentations of the underlying CT data. All interactive procedures such as bone and soft tissue repositioning are performed under the guidance of the modeling system which feeds the processed geometry into the FEM solver. The resulting shape is generated from minimizing the global energy of the surface under the presence of external forces. Photorealistic pictures are obtained from rendering the facial surface with the advanced animation system on which this prototype is built.Although we do not claim any of the presented algorithms themselves to be new, the synthesis of several methods offers a new facial model quality. Our concept is a significant extension to existing ones and, due to its versatility, can be employed in different applications such as facial animation, facial reconstruction, or the simulation of aging. We illustrate features of our system with some examples from the Visible Human Data Set. TM

ABSTRACT

This paper describes a new method for visualization and analysis of multivariate laser range data using complex-valued non-orthogonal Gabor wavelets, principal component analysis and a topological mapping network. The initial data set that provides both shape and texture information is encoded in terms of both amplitude and phase of a complex valued 2D image function. A set of carefully designed oriented Gabor filters performs a decomposition of the data and allows for retrieving local shape and texture features. The feature vector obtained from this method is multidimensional and in order to evaluate similar data features, further subspace methods to transform the data onto visualizable attributes, such as R,G,B, have to be determined. For this purpose, a feature-based visualization pipeline is proposed consisting of principal component analysis, normalization and a topological mapping network. This process finally renders a R,G,B subspace representation of the multidimensional feature vector. Our method is primarily applied to the visual analysis of features in human faces-but is not restricted to that.

The porcine glottis differs from the human glottis in its cranial and caudal vocal folds (CraF, CauF). The fibre apparatus of these folds was studied histomorphometrically in adult minipigs. For object definition and quantification, the colour-selection tools of the Adobe-Photoshop program were used. Another key feature was the subdivision of the cross-sections of the folds into proportional subunits. This allowed a statistical analysis irrespective of differences in thickness of the folds. Both folds had a distinct, dense subepithelial layer equivalent to the basement membrane zone in humans. The subsequent, loose layer was interpreted - in principle - as being equivalent to Reinke's space of the human vocal fold. The next two layers were not clearly separated. Due to this, the concept of a true vocal ligament did not appear applicable to neither CauF nor CraF. Instead, the body-cover model was emphasized by our findings. The missing vocalis muscle in the CraF is substituted by large collagen fibre bundles in a proportional depth corresponding to the position of the muscle of the CauF. The distribution of elastic fibres made the CraF rather than the CauF more similar to the human vocal fold. We suggest that these data are useful for those wishing to use the porcine glottis as a model for studying oscillatory properties during phonation.

The accurate prediction of the post-surgical facial shape is of paramount importance for surgical planning in facial surgery. In this paper we present a framework for facial surgery simulation which is based on volumetric finite element modeling. We contrast conventional procedures for surgical planning against our system by accompanying a patient during the entire process of planning, medical treatment and simulation. In various preprocessing steps a 3D physically based facial model is reconstructed from CT and laser range scans. All geometric and topological changes are modeled interactively using Alias.™ Applying fully 3D volumetric elasticity allows us to represent important volumetric effects such as incompressibility in a natural and physically accurate way. For computational efficiency, we devised a novel set of prismatic shape functions featuring a globally C 1 -continuous surface in combination with a C 0 interior. Not only is it numerically accurate, but this construction enables us to compute smooth and visually appealing facial shapes.