scispace - formally typeset
Proceedings ArticleDOI

Exploring vector fields with distribution-based streamline analysis

TLDR
It is shown that statistical distributions of measurements along the trajectory of a streamline can be used as a robust and effective descriptor to measure the similarity between streamlines.
Abstract
Streamline-based techniques are designed based on the idea that properties of streamlines are indicative of features in the underlying field. In this paper, we show that statistical distributions of measurements along the trajectory of a streamline can be used as a robust and effective descriptor to measure the similarity between streamlines. With the distribution-based approach, we present a framework for interactive exploration of 3D vector fields with streamline query and clustering. Streamline queries allow us to rapidly identify streamlines that share similar geometric features to the target streamline. Streamline clustering allows us to group together streamlines of similar shapes. Based on user's selection, different clusters with different features at different levels of detail can be visualized to highlight features in 3D flow fields. We demonstrate the utility of our framework with simulation data sets of varying nature and size.

read more

Citations
More filters
Journal ArticleDOI

FlowNet: A Deep Learning Framework for Clustering and Selection of Streamlines and Stream Surfaces

TL;DR: FlowNet is presented, a single deep learning framework for clustering and selection of streamlines and stream surfaces generated from a flow field data set and which employs an autoencoder to learn their respective latent feature descriptors.
Journal ArticleDOI

Analysis and Visualization of Discrete Fracture Networks Using a Flow Topology Graph

TL;DR: An analysis and visualization prototype using the concept of a flow topology graph (FTG) for characterization of flow in constrained networks, with a focus on discrete fracture networks (DFN), developed collaboratively by geoscientists and visualization scientists is presented.
Journal ArticleDOI

A Survey of Seed Placement and Streamline Selection Techniques

TL;DR: This state‐of‐the‐art report analyzes and classify seed placement and streamline selection (SPSS) techniques used by the scientific flow visualization community, and evaluates the identified strategy groups with respect to focus on regions of interest, minimization of redundancy, and overall computational performance.
Proceedings ArticleDOI

Streamline similarity analysis using bag-of-features

TL;DR: A novel streamline similarity comparison method inspired by the bag-of-features idea from computer vision, which computes a feature vector, spatially sensitive bag- of-features, for each streamline as its signature to measure the similarity between two streamlines in an efficient and accurate way.
Journal ArticleDOI

Extracting flow features via supervised streamline segmentation

TL;DR: An effective heuristic which captures how human beings segment streamlines is proposed, based on the minimum bounding ellipsoid volume, to help determine where to segment a streamline.
References
More filters
Journal ArticleDOI

On the identification of a vortex

TL;DR: In this article, the authors propose a definition of vortex in an incompressible flow in terms of the eigenvalues of the symmetric tensor, which captures the pressure minimum in a plane perpendicular to the vortex axis at high Reynolds numbers, and also accurately defines vortex cores at low Reynolds numbers.
Journal ArticleDOI

The String-to-String Correction Problem

TL;DR: An algorithm is presented which solves the string-to-string correction problem in time proportional to the product of the lengths of the two strings.
Proceedings Article

Using dynamic time warping to find patterns in time series

TL;DR: Preliminary experiments with a dynamic programming approach to pattern detection in databases, based on the dynamic time warping technique used in the speech recognition field, are described.
Proceedings ArticleDOI

A metric for distributions with applications to image databases

TL;DR: This paper uses the Earth Mover's Distance to exhibit the structure of color-distribution and texture spaces by means of Multi-Dimensional Scaling displays, and proposes a novel approach to the problem of navigating through a collection of color images, which leads to a new paradigm for image database search.
Related Papers (5)