Simulating facial surgery

Surgery simulation is a growing field of research comprising the efforts of various disciplines including Computer Graphics, Computer Vision, Medicine, Mechanics, Robotics and even Animation. We try to combine, adapt and extend different solutions to this problem and re-assemble them using mid-range 3D graphics hardware, modern object-oriented methods and free visualization toolkits. Reconstructions of the physically based realistic 3D models are achieved from CT scans. in particular, we focus on the generic model concept, an evolving method to encapsulate generic informations in a generic 3D mesh. This model is subsequently deformed using multivariate scattered data interpolation techniques so that it matches the reconstructed model of the patient being studied, under the control of common landmark points. We describe a way to build a topological relationship (a bridge) between these non-related geometrical and topological models, thus opening a framework to transfer different kind of generic informations, ranging from algorithmic simplification and computation hints to anatomical features or learning material. Starting from several uncalibrated photographs, we also show how 2D features points may be used to recover the camera parameters and employ them as control points to deform our model in a similar fashion, so that the texture informations is retrieved after projecting the model into the photographic pose.