Multi-scale visual analysis of cycle characteristics in spatially-embedded graphs

We present a visual analysis environment based on a multi-scale partitioning of a 2d domain into regions bounded by cycles in weighted planar embedded graphs. The work has been inspired by an application in granular materials research, where the question of scale plays a fundamental role in the anal...

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Bibliographic Details
Published in:Visual informatics (Online) 2023-09, Vol.7 (3), p.49-58
Main Authors: Rasheed, Farhan, Masood, Talha Bin, Murthy, Tejas G., Natarajan, Vijay, Hotz, Ingrid
Format: Article
Language:English
Subjects:
Computational geometry
Force loops
Force network
Granular materials
Persistence homology
Planar graph
Visual data analysis
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Summary:We present a visual analysis environment based on a multi-scale partitioning of a 2d domain into regions bounded by cycles in weighted planar embedded graphs. The work has been inspired by an application in granular materials research, where the question of scale plays a fundamental role in the analysis of material properties. We propose an efficient algorithm to extract the hierarchical cycle structure using persistent homology. The core of the algorithm is a filtration on a dual graph exploiting Alexander’s duality. The resulting partitioning is the basis for the derivation of statistical properties that can be explored in a visual environment. We demonstrate the proposed pipeline on a few synthetic and one real-world dataset.
ISSN:2468-502X
2468-502X
DOI:10.1016/j.visinf.2023.06.005