CCF CAD/CG 2023 |
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Focus+Context visualization based on optimal mass transportation |
Kehua SU1(),Bailüe LIU1,Na LEI2(),Kehan LI1,Xianfeng GU3 |
1.School of Computer Science,Wuhan University,Wuhan 430072,China 2.International School of Information Science & Engineering,Dalian University of Technology,Dalian 116024,Liaoning Province,China 3.Department of Computer Science,State University of New York at Stony Brook,Stony Brook 11790,New York,USA |
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Abstract In visualization field, Focus+Context techniques have been developed to visualize large, complex models on the display device with limited resolution. In this work, we propose a novel method for Focus+Context visualization based on optimal mass transportation. An optimal mass transportation map deforms a volume to itself, transforms the source measure (volumetric element) to the target measure with the minimal transportation cost. Solving the optimal mass transportation problem is equivalent to a convex optimization, and can be converted to computing power Voronoi diagrams in classical computational geometry. Comparing to existing approaches, the proposed method has solid theoretic foundation, which guarantees the existence, uniqueness and the smoothness of the solution. It allows the user to accurately control the target measure, and select multiple focus regions with irregular shapes. The resulting deformation is globally smooth and flipping free. Experiments with several volume data sets from medical applications and scientific simulations demonstrate the effectiveness and efficiency of our method.
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Received: 12 June 2023
Published: 30 November 2023
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Corresponding Authors:
Na LEI
E-mail: skh@whu.edu.cn;nalei@dlut.edu.cn
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Cite this article:
Kehua SU,Bailüe LIU,Na LEI,Kehan LI,Xianfeng GU. Focus+Context visualization based on optimal mass transportation. Journal of Zhejiang University (Science Edition), 2023, 50(6): 681-691.
URL:
https://www.zjujournals.com/sci/EN/Y2023/V50/I6/681
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基于最优质量传输的Focus+Context可视化
在分辨率有限的显示设备上,Focus+Context技术可用于大型复杂模型的可视化。提出了一种基于最优质量传输的Focus+Context可视化方法。通过最优质量传输映射,对自身进行体积变形,将源测度(体素)转换为传输成本最小的目标测度;将求解最优质量传输问题等价于凸优化过程,转换为计算几何中经典的幂Voronoi图计算。与现有方法相比,本文方法具有坚实的理论基础,保证了解的存在性、唯一性和平滑性;允许用户精确控制目标测度,选择多个形状不规则的聚焦区域,使产生的变形是全局平滑的,并可自由翻转。用于自医学应用和科学仿真的几项体数据集,证明了所提方法是有效和高效的。
关键词:
辐射度,
全局光照,
常量时间
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