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음함수 곡면의 날카로운 형상 가시화를 위한 확장 Adaptively Sampled Distance Fields 방법
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  • 음함수 곡면의 날카로운 형상 가시화를 위한 확장 Adaptively Sampled Distance Fields 방법
저자명
차주환,이규열,김태완,Cha. J.H.,Lee. K.Y.,Kim. T.W.
간행물명
한국CAD/CAM학회논문집
권/호정보
2005년|10권 1호|pp.27-39 (13 pages)
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한국CAD/CAM학회
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정기간행물|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Implicit surfaces are geometric shapes which are defined by implicit functions and exist in three-dimensional space. Recently, implicit surfaces have received much attention in solid modeling applications because they are easy to represent the location of points and to use boolean operations. However, it is difficult to chart points on implicit surfaces for rendering. As efficient rendering method of implicit surfaces, the original Adaptively Sampled Distance Fields (ADFs) $method^{[1]}$ is to use sampled distance fields which subdivide the three dimensional space of implicit surfaces into many cells with high sampling rates in regions where the distance field contains fine detail and low sampling rates where the field varies smoothly. In this paper, in order to maintain the sharp features efficiently with small number of cells, an extended ADFs method is proposed, applying the Dual/Primal mesh optimization $method^{[2]}$ to the original ADFs method. The Dual/Primal mesh optimization method maintains sharp features, moving the vertices to tangent plane of implicit surfaces and reconstructing the vertices by applying a curvature-weighted factor. The proposed extended ADFs method is applied to several examples of implicit surfaces to evaluate the efficiency of the rendering performance.