Topological feature extraction and tracking

Bremer, Peer-Timo; Bringa, Eduardo M.; Duchaineau, Mark A.; Gyulassy, Attila; Laney, Dan; Mascarenhas, Ajith; Pascucci, Valerio

doi:10.1088/1742-6596/78/1/012007

Cited by 37 publications

(33 citation statements)

References 8 publications

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“…Bremer et al [3] survey methods and applications of topological feature tracking in molecular analysis, combustion simulations, and porous materials analysis. The results are shown as feature tracks embedded in the original domain.…”

Section: Related Workmentioning

confidence: 99%

Computing and Visualizing Time-Varying Merge Trees for High-Dimensional Data

Oesterling¹,

Heine

Weber

et al. 2017

Mathematics and Visualization

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We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree-a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.

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Section: Related Workmentioning

confidence: 99%

Computing and Visualizing Time-Varying Merge Trees for High-Dimensional Data

Oesterling¹,

Heine

Weber

et al. 2017

Mathematics and Visualization

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show abstract

“…For example, contour trees were applied for isosurfaces and volume rendering [8,26] and Jacobi sets and Reeb graphs were used track volumetric features and quantities over time [4,5,27].…”

Section: Related Workmentioning

confidence: 99%

A Comparison of Pareto Sets and Jacobi Sets

Huettenberger

Garth

2014

Mathematics and Visualization

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“…The basic stages for corresponding interest points between images include: (1) interest point detection, (2) description, and (3) matching. After these steps, (4) filtration (as SIFT-ratio) and (5) model fitting (RANSAC) are commonly used.…”

Section: Introductionmentioning

confidence: 99%