Abstract

The purpose of visualization is to gain understanding of 3D structures through images. Although many rendering techniques have been proposed for this purpose, the effective visualization remains a challenging task, due to occlusion, clutter, noise in the data, and acquisition pose. Recent solutions to this problem deal with transfer functions and other rendering techniques to enhance the visibility of certain parts of interest. At the core of these techniques is the assumption that the user's role is passive and that the data remains unchanged. In this thesis, we explore a more active approach to visualization, where a scientist can manipulate a dataset as if deforming a real model. We call this type of manipulation Illustrative Deformation. Our approach draws the name from the types of deformations that are often depicted in scientific illustration, which are used to enhance visibility of certain features while providing context, or to abstract the structure of an object or procedure. Inspired by medical and surgical illustration, our approach was designed to reproduce some of their key properties: illustrations often contains cuts and dissections, they allow feature-sensitive operations, which can be applied to a semantic component of the object without affecting other parts of the object, and they enable virtual operations, which do not necessarily conform to reality, but are useful for understanding the structure of complex objects. Our approach is based on a generalized notion of 3D displacement maps, which unifies the specification of continuous and discontinuous deformations on both volumes and surface-based objects. We show how displacements can describe a wide range of transformations, including cuts and peels, how they can be extended to include feature-sensitive operations, and how can they be implemented to obtain high quality interactive rendering on commodity hardware. We also show how our approach can be extended to the deformation of surface-based models without the need for remeshing. Through a number of examples and quantitative results, we demonstrate the generality, flexibility and scalability of our approach, and we explore its applications in medical illustration, surgical planning and simulation, and as a general tool for visualization and computer graphics.

Full Text
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