• Journal of Korea Multimedia Society
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• v.18 no.5
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• pp.671-681
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• 2015

This paper presents an extended scientific visualization for the public over the scientific visualization targeting for scientists. Our scientific visualization pursues both transmission of scientific information and good-looking visuals. First of all, we examine a tendency to produce scientific images that make the public understand science, even though they are not professional scientists. As a result, we can find several cases that actively generate scientific visualizations for the public. Among them, several research institutes possess own production studio. As the production of scientific images is a convergence field combined of art and science, cooperation between artists and scientists is necessary. Therefore, in-depth communication between them is essential at the planning stage. Moreover, continuous feedbacks between two groups in the production stage, the next stage of the planning, make the scientific visualization to perfection. In this paper, we present 2 modeling methods that are easily encountered during producing scientific visualizations and shading and rendering methods for generating photorealistic images. The concept of an extended scientific visualization that we present shows a new vision of the scientific visualization field.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.11-18
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• 1997

Scientific volume visualization addresses the representation, manipulation, and rendering of volumetric data sets, providing mechanisms for looking closely into structures and understanding their complexity and dynamics. In the past several years, a tremendous amount of research and development has been directed toward algorithms and data modeling methods for a scientific data visualization. But there has been very little work on developing a mathematical volume model that feeds this visualization. Especially, in flow visualization, the volume model has long been required as a guidance to display the very large amounts of data resulting from numerical simulations. In this paper, we focus on the mathematical representation of volumetric data sets and the method of extracting meaningful information from the derived volume model. For this purpose, a B-spline volume is extended to a high dimensional trivariate model which is called as a flow visualization model in this paper. Two three-dimensional examples are presented to demonstrate the capabilities of this model.