Pathline glyphs

Hlawatsch, Marcel; Sadlo, Filip; Jang, Han-Ul; Weiskopf, Daniel

doi:10.1111/cgf.12335

Cited by 7 publications

(3 citation statements)

References 19 publications

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“…The transport and vortical behaviors in unsteady flow can also be studied via analyzing various attributes associated with pathlines [2,34]. These attributes can be utilized for pathline and streak line placement [3], and glyph design [35]. Local analysis of unsteady flow Local analysis of flow focuses on small-scale behaviors, such as local volume dilation, compression, infinitesimal rotation, stretching, shearing, acceleration and momentum.…”

Section: Related Workmentioning

confidence: 99%

Visual Analysis of Spatia-temporal Relations of Pairwise Attributes in Unsteady Flow

Berenjkoub

Ostilla–Mónico

Laramee

et al. 2019

IEEE Trans. Visual. Comput. Graphics

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Despite significant advances in the analysis and visualization of unsteady flow, the interpretation of it's behavior still remains a challenge. In this work, we focus on the linear correlation and non-linear dependency of different physical attributes of unsteady flows to aid their study from a new perspective. Specifically, we extend the existing spatial correlation quantification, i.e. the Local Correlation Coefficient (LCC), to the spatio-temporal domain to study the correlation of attribute-pairs from both the Eulerian and Lagrangian views. To study the dependency among attributes, which need not be linear, we extend and compute the mutual information (MI) among attributes over time. To help visualize and interpret the derived correlation and dependency among attributes associated with a particle, we encode the correlation and dependency values on individual pathlines. Finally, to utilize the correlation and MI computation results to identify regions with interesting flow behavior, we propose a segmentation strategy of the flow domain based on the ranking of the strength of the attributes relations. We have applied our correlation and dependency metrics to a number of 2D and 3D unsteady flows with varying spatio-temporal kernel sizes to demonstrate and assess their effectiveness.

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Section: Related Workmentioning

confidence: 99%

Visual Analysis of Spatia-temporal Relations of Pairwise Attributes in Unsteady Flow

Berenjkoub

Ostilla–Mónico

Laramee

et al. 2019

IEEE Trans. Visual. Comput. Graphics

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“…31 Glyph based designs have been proven to be effective for representing rich data in a wide range of domains. Examples include visualizing poetry, 32 sport event, 33 medical data, [34][35][36] time series data, 37 workflow data, 38 vector fields, 39,40 or representing data uncertainty 41 or sensitivity 42 and comparing subject survey data. 43 A glyph's composite visual form makes it suitable to be used in distinguishing some sort of ''activities'' in a dynamic environment.…”

Section: Glyph-based Visualizationmentioning

confidence: 99%

Z-Glyph: Visualizing outliers in multivariate data

Cao

Lin

Gotz

et al. 2017

Information Visualization

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Outlier analysis techniques are extensively used in many domains such as intrusion detection. Today, even with the most advanced statistical learning techniques, human judgment still plays an important role in outlier analysis tasks due to the difficulty of defining and collecting outlier examples. This work seeks to tackle this problem by introducing a new visualization design, “Z-Glyph,” a family of glyphs designed to facilitate human judgment in outlier analysis of multivariate data. By employing a location-scale transformation, a Z-Glyph represents the “normal” data using regular shapes (e.g. straight line and circle), such that the abnormal data can be revealed when deviating from the regular shapes. Extensive controlled experiment and case studies based on real-world datasets indicate the superior performance of the Z-Glyph family, compared with the baselines, suggesting that the proposed design is able to leverage human perceptional features with statistical characterization. This study contributes to a more fundamental understanding about designing visual representations for revealing outliers in multivariate data, which can be applied as a building block in many domain-specific anomaly detection applications.

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“…Glyph Design To avoid this problem, we design an interactive glyph visualization that is rendered progressively and adaptive to the current view. Glyphs are frequently applied in flow visualization, e.g., in [HLNW11, HSJW14]. See the recent reports on glyph design by Ward [War08] and Borgo et al [BKC*13] for an overview.…”

Section: Glyph‐based Visualization Of Asymptotic Behaviormentioning

confidence: 99%

Inertial Steady 2D Vector Field Topology

Günther¹,

Theisel²

2016

Computer Graphics Forum

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Figure 1: Visualization of inertial critical points and a glyph-based visualization of the asympotic behavior of inertial particles. The sink (blue critical point) that is reached by an inertial particle depends on its initial position x 0 and the initial velocity v 0 . The glyph location encodes x 0 and the glyph disc color-codes the sink that is reached for a certain v 0 . The glyph center represents v 0 = 0 and the selected glyph is enlarged in the bottom right corner, showing the seeds of inertial particle trajectories. Left: BORROMEAN RINGS with particle diameter dp = 70 µm and maximal velocity vmax = 10 m/s (occurs at glyph boundary), middle: DUFFING OSCILLATOR with dp = 100 µm, vmax = 5 m/s, and right: NINE CP with dp = 70 µm, vmax = 10 m/s. Inertial critical point types are listed in Table 1. AbstractVector field topology is a powerful and matured tool for the study of the asymptotic behavior of tracer particles in steady flows. Yet, it does not capture the behavior of finite-sized particles, because they develop inertia and do not move tangential to the flow. In this paper, we use the fact that the trajectories of inertial particles can be described as tangent curves of a higher dimensional vector field. Using this, we conduct a full classification of the first-order critical points of this higher dimensional flow, and devise a method to their efficient extraction. Further, we interactively visualize the asymptotic behavior of finite-sized particles by a glyph visualization that encodes the outcome of any initial condition of the governing ODE, i.e., for a varying initial position and/or initial velocity. With this, we present a first approach to extend traditional vector field topology to the inertial case.

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Pathline glyphs

Cited by 7 publications

References 19 publications

Visual Analysis of Spatia-temporal Relations of Pairwise Attributes in Unsteady Flow

Visual Analysis of Spatia-temporal Relations of Pairwise Attributes in Unsteady Flow

Z-Glyph: Visualizing outliers in multivariate data

Inertial Steady 2D Vector Field Topology

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