YMCA — Your mesh comparison application

YMCA — Your mesh comparison application
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YMCA — 您的网格比较应用程序

DOI:
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发表时间:
2014
期刊:
IEEE Conference on Visual Analytics Science and Technology
影响因子:
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通讯作者:
S. Bruckner
S. Bruckner
中科院分区:
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文献类型:
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作者:
Johanna Schmidt;R. Preiner;T. Auzinger;M. Wimmer;E. Gröller;S. Bruckner

文献摘要

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多边形网格可以用几种不同的方式创建。在本文中,我们主要研究从点云中重建网格,点云是三维中的点集。已经有几种算法可以处理这个任务,但它们有不同的优点和缺点,这导致了大量可能的重建结果(即网格)。这些技术的评估需要在不同网格之间进行广泛的比较,到目前为止,通过将渲染网格的图像并排放置或通过热图编码差异来完成。这两种方法的一个主要缺点是它们不能很好地扩展网格数量。本文介绍了一种新的三维网格比较视觉分析技术,它可以同时比较几个网格,并允许对它们的差异进行交互式探索。我们的方法概述了2D视图中输入网格的差异。通过选择某些感兴趣的区域,用户可以切换到3D表示,并详细探索空间差异。为了检查局部变化,我们提供了一个神奇的3D镜头工具。透镜的位置和尺寸提供了在选定区域重建变化的进一步信息。利用我们的比较可视化方法,可以很容易地定位和检查几种网格重建算法之间的差异。
Polygonal meshes can be created in several different ways. In this paper we focus on the reconstruction of meshes from point clouds, which are sets of points in 3D. Several algorithms that tackle this task already exist, but they have different benefits and drawbacks, which leads to a large number of possible reconstruction results (i.e., meshes). The evaluation of those techniques requires extensive comparisons between different meshes which is up to now done by either placing images of rendered meshes side-by-side, or by encoding differences by heat maps. A major drawback of both approaches is that they do not scale well with the number of meshes. This paper introduces a new comparative visual analysis technique for 3D meshes which enables the simultaneous comparison of several meshes and allows for the interactive exploration of their differences. Our approach gives an overview of the differences of the input meshes in a 2D view. By selecting certain areas of interest, the user can switch to a 3D representation and explore the spatial differences in detail. To inspect local variations, we provide a magic lens tool in 3D. The location and size of the lens provide further information on the variations of the reconstructions in the selected area. With our comparative visualization approach, differences between several mesh reconstruction algorithms can be easily localized and inspected.