极值图之间的距离

V. Narayanan, Dilip Mathew Thomas, V. Natarajan
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引用次数: 30

摘要

科学现象通常是通过对同一现象的不同观测产生的相关标量场的集合来研究的。对这些数据的探索需要一个强大的距离度量来比较标量字段,以完成诸如识别关键事件和建立数据中特征之间的对应关系等任务。为了实现这一目标,我们提出了一种称为完全极值图的拓扑数据结构,并在其上定义了一个距离度量,用于以特征感知的方式比较标量场。我们设计了一种计算距离的算法,并展示了它在时变数据分析中的应用。
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Distance between extremum graphs
Scientific phenomena are often studied through collections of related scalar fields generated from different observations of the same phenomenon. Exploration of such data requires a robust distance measure to compare scalar fields for tasks such as identifying key events and establishing correspondence between features in the data. Towards this goal, we propose a topological data structure called the complete extremum graph and define a distance measure on it for comparing scalar fields in a feature-aware manner. We design an algorithm for computing the distance and show its applications in analysing time varying data.
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