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Subdomain aware contour trees and contour evolution in time-dependent scalar fields

机译:依赖时间的标量场中子域感知轮廓树和轮廓演化

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For time-dependent scalar fields, one is often interested in topology changes of contours in time. In this paper, we focus on describing how contours split and merge over a certain time interval. Rather than attempting to describe all individual contour splitting and merging events, we focus on the simpler and therefore more tractable in practice problem: describing and querying the cumulative effect of the splitting and merging events over a user-specified time interval. Using our system one can, for example, find all contours at time t/sub 0/ that continue to two contours at time t/sub 1/ without hitting the boundary of the domain. For any such contour, there has to be a bifurcation happening to it somewhere between the two times, but, in addition to that, many other events may possibly happen without changing the cumulative outcome (e.g. merging with several contours born after t/sub 0/ or splitting off several contours that disappear before t/sub 1/). Our approach is flexible enough to enable other types of queries, if they can be cast as counting queries for numbers of connected components of intersections of contours with certain simply connected domains. Examples of such queries include finding contours with large life spans, contours avoiding certain subset of the domain over a given time interval or contours that continue to two at a later time and then merge back to one some time later. Experimental results show that our method can handle large 3D (2 space dimensions plus time) and 4D (3D+time) datasets. Both preprocessing and query algorithms can easily be parallelized.
机译:对于与时间有关的标量场,人们通常会对轮廓的时间拓扑变化感兴趣。在本文中,我们专注于描述轮廓在特定时间间隔内如何分裂和合并。与其尝试描述所有单独的轮廓分裂和合并事件,我们不着重于实践中更简单,因此更易处理的问题:描述和查询在用户指定的时间间隔内分裂和合并事件的累积效果。例如,使用我们的系统,可以找到时间t / sub 0 /处的所有轮廓,并在时间t / sub 1 /处找到两个轮廓,而不会触及域的边界。对于任何这样的轮廓,它必须在两次之间的某个位置发生分叉,但是除此之外,在不改变累积结果的情况下,可能还会发生许多其他事件(例如,合并t / sub 0之后出生的几个轮廓) /或分割出在t / sub 1 /)之前消失的几个轮廓。我们的方法足够灵活,可以启用其他类型的查询,前提是可以将它们转换为对具有某些简单连接域的轮廓相交的连接分量数进行计数的查询。这样的查询的示例包括查找具有较大寿命的轮廓,在给定的时间间隔内避免该域的某些子集的轮廓,或在以后的时间继续为两个,然后在一段时间后合并为一个的轮廓。实验结果表明,我们的方法可以处理大型3D(2维空间加上时间)和4D(3D +时间)数据集。预处理算法和查询算法都可以轻松并行化。

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