Proceedings ArticleDOI
Exploring vector fields with distribution-based streamline analysis
Kewei Lu,Abon Chaudhuri,Teng-Yok Lee,Han-Wei Shen,Pak Chung Wong +4 more
- pp 257-264
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
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Journal ArticleDOI
FlowNet: A Deep Learning Framework for Clustering and Selection of Streamlines and Stream Surfaces
Jun Han,Jun Tao,Chaoli Wang +2 more
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
Garrett Aldrich,Jeffrey D. Hyman,Satish Karra,Carl W. Gable,Nataliia Makedonska,Hari S. Viswanathan,Jonathan Woodring,Bernd Hamann +7 more
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
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