A Concise Introduction to Scientific Visualization by Brad Eric Hollister & Alex Pang
Author:Brad Eric Hollister & Alex Pang
Language: eng
Format: epub
ISBN: 9783030864194
Publisher: Springer International Publishing
Basic lighting of surfaces require diffuse and specular light [22] (Fig. 5), which determines color and intensity over a surface. After lighting, texture from image data may be provided as described. While meant initially for realistic imagery, textures may be utilized to represent more abstract information about scene geometry, such as data from scientific computation not otherwise visible.
Fig. 5The Phong reflection model.
From [Brad Smith, Wikimedia Commons]
Silicon Graphics
While computer-generated imagery was developing quickly throughout the 1970s, computational bottlenecks were still preventing the rendering of sufficient data at interactive rates. For CG to be a viable tool for scientific visualization, the movement of the rendering pipeline from software, to hardware, was an important next step.
Another doctoral graduate of the University of Utah, James Clark, perhaps a more controversial figure than Jim Blinn [23], was arguably more influential in the general adoption of computers for graphical applications. While as an Assistant Professor at the University of California at Santa Cruz, he began publishing research aimed at increasing the efficiency of the raster pipeline, the first of which was âHierarchical Geometric Models for Visible Surface Algorithmsâ [24]. In this paper, he presented methods to cull geometry that do not contribute to the visible part of a scene, thereby speeding up the pipeline. He later went on to found Silicon Graphics, a company that produced graphical workstations.
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Biomathematics | Differential Equations |
Game Theory | Graph Theory |
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