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

作　　者：Farhan Rasheed Talha Bin Masood Tejas G.Murthy Vijay Natarajan Ingrid Hotz 

机构地区：[1]Department of Science and Technology,LinkOing University,Bredgatan 33,NorrkOing,60221,Sweden [2]Department of Civil Engineering,Indian Institute of Science,Bangalore,560012,India [3]Department of Computer Science and Automation,Indian Institute of Science,Bangalore,560012,India

出　　处：《Visual Informatics》2023年第3期49-58,共10页可视信息学（英文）

基　　金：the Wallenberg AI,Autonomous Systems and Software Program(WASP)funded by the Knut and Alice Wallenberg Foundation,the SeRC(Swedish e-Science Research Center)and the ELLIIT environment for strategic research in Sweden,the Swedish Research Council(VR)grant 2019–05487;an Indo-Swedish joint network project:DST/INT/SWD/VR/P-02/2019 VR grant 2018–07085.

摘　　要：We present a visual analysis environment based on a multi-scale partitioning of a 2d domain intoregions bounded by cycles in weighted planar embedded graphs.The work has been inspired by anapplication in granular materials research,where the question of scale plays a fundamental role inthe analysis of material properties.We propose an efficient algorithm to extract the hierarchical cyclestructure using persistent homology.The core of the algorithm is a filtration on a dual graph exploitingAlexander’s duality.The resulting partitioning is the basis for the derivation of statistical properties thatcan be explored in a visual environment.We demonstrate the proposed pipeline on a few syntheticand one real-world dataset.

关 键 词：Visual data analysis Planar graph Force network Granular materials Persistence homology Force loops Computational geometry 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]