The tutorial presents state-of-the-art visualization techniques inspired by traditional technical and medical illustrations. Such techniques exploit the perception of the human visual system and provide effective visu...
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ISBN:
(纸本)0780394623
The tutorial presents state-of-the-art visualization techniques inspired by traditional technical and medical illustrations. Such techniques exploit the perception of the human visual system and provide effective visual abstractions to make the visualization clearly understandable. Visual emphasis and abstraction has been used for expressive presentation from prehistoric paintings to nowadays scientific and medical illustrations. Many of the expressive techniques used in art are adopted in computergraphics, and are denoted as illustrative or non-photorealistic rendering. Different stroke techniques, or brush properties express a particular level of abstraction. Feature emphasis or feature suppression is achieved by combining different abstraction levels in illustrative rendering. Challenges in visualization research are very large data visualization as well as multi-dimensional data visualization. To effectively convey the most important visual information there is a significant need for visual abstraction. For less relevant information the dedicated image space is reduced to enhance more prominent features. The discussed techniques in the context of scientific visualization are based on iso-surfaces and volume rendering. Apart from visual abstraction, i.e., illustrative representation, the visibility of prominent features can be achieved by illustrative visualization techniques such as cut-away views or ghosted views. The structures that occlude the most prominent information are suppressed in order to clearly see more interesting parts. A different smart way to provide information on the data is using exploded views or other types of deformation. Furthermore intuitive feature classification via 3D painting and manipulation with the classified data including label placement is presented. Discussed non-photorealistic and illustrative techniques from visualization and graphics are shown from the perspective as tools for illustrators from medicine, botany, archeology
The classification of volumetric data sets as well as their rendering algorithms are typically based on the representation of the underlying grid. Grid structures based on a Cartesian lattice are the de-facto standard...
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ISBN:
(纸本)0780372018
The classification of volumetric data sets as well as their rendering algorithms are typically based on the representation of the underlying grid. Grid structures based on a Cartesian lattice are the de-facto standard for regular representations of volumetric data. In this paper we introduce a more general concept of regular grids for the representation of volumetric data. We demonstrate that a specific type of regular lattice-the so-called body-centered cubic-is able to represent the same data set as a Cartesian grid to the same accuracy but with 29.3% fewer samples. This speeds up traditional volume rendering algorithms by the same ratio, which we demonstrate by adopting a splatting implementation for these new lattices. We investigate different filtering methods required for computing the normals on this lattice. The lattice representation results also in lossless compression ratios that are better than previously reported. Although other regular grid structures achieve the same sample efficiency, the body-centered cubic is particularly easy to use. The only assumption necessary is that the underlying volume is isotropic and band-limited-an assumption that is valid for most practical data sets.
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