Fast Fiber Line Extraction for 2D Bivariate Scalar Fields

TL;DR

This paper introduces a fast algorithm for extracting fiber lines from 2D bivariate scalar fields, significantly improving interactivity in visualization tasks by outperforming existing methods in speed.

Contribution

The authors present a novel joint traversal algorithm for fiber line extraction in 2D bivariate data, achieving substantial speed improvements over prior approaches.

Findings

Speedup of several orders of magnitude over naive methods

Requires two thirds of the computation time compared to adapted existing methods

Effective across various datasets and configurations

Abstract

Extracting level sets from scalar data is a fundamental operation in visualization with many applications. Recently, the concept of level set extraction has been extended to bivariate scalar fields. Prior work on vector field equivalence, wherein an analyst marks a region in the domain and is shown other regions in the domain with similar vector values, pointed out the need to make this extraction operation fast, so that analysts can work interactively. To date, the fast extraction of level sets from bivariate scalar fields has not been researched as extensively as for the univariate case. In this paper, we present a novel algorithm that extracts fiber lines, i.e., the preimages of so called control polygons (FSCP), for bivariate 2D data by joint traversal of bounding volume hierarchies for both grid and FSCP elements. We performed an extensive evaluation, comparing our method to a two-dimensional adaptation of the method proposed by Klacansky et al., as well as to the naive approach for fiber line extraction. The evaluation incorporates a vast array of configurations in several datasets. We found that our method provides a speedup of several orders of magnitudes compared to the naive algorithm and requires two thirds of the computation time compared to Klacansky et al. adapted for 2D.