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An Empirical Evaluation of Visual Cues for 3D Flow Field Perception.

Record Type:	Electronic resources : Monograph/item
Title/Author:	An Empirical Evaluation of Visual Cues for 3D Flow Field Perception./
Author:	Stevens, Andrew Harlan.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:	143 p.
Notes:	Source: Dissertations Abstracts International, Volume: 83-01, Section: B.
Contained By:	Dissertations Abstracts International83-01B.
Subject:	Computer science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28318746
ISBN:	9798516963186

An Empirical Evaluation of Visual Cues for 3D Flow Field Perception.
Stevens, Andrew Harlan.

An Empirical Evaluation of Visual Cues for 3D Flow Field Perception. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 143 p.

Source: Dissertations Abstracts International, Volume: 83-01, Section: B.

Thesis (Ph.D.)--University of New Hampshire, 2021.

This item must not be sold to any third party vendors.

Three-dimensional vector fields are common datasets throughout the sciences. They often represent physical phenomena that are largely invisible to us in the real world, like wind patterns and ocean currents. Computer-aided visualization is a powerful tool that can represent data in any way we choose through digital graphics. Visualizing 3D vector fields is inherently difficult due to issues such as visual clutter, self-occlusion, and the difficulty of providing depth cues that adequately support the perception of flow direction in 3D space. Cutting planes are often used to overcome these issues by presenting slices of data that are more cognitively manageable. The existing literature provides many techniques for visualizing the flow through these cutting planes; however, there is a lack of empirical studies focused on the underlying perceptual cues that make popular techniques successful. The most valuable depth cue for the perception of other kinds of 3D data, notably 3D networks and 3D point clouds, is structure-from-motion (also called the Kinetic Depth Effect); another powerful depth cue is stereoscopic viewing, but none of these cues have been fully examined in the context of flow visualization. This dissertation presents a series of quantitative human factors studies that evaluate depth and direction cues in the context of cutting plane glyph designs for exploring and analyzing 3D flow fields. The results of the studies are distilled into a set of design guidelines to improve the effectiveness of 3D flow field visualizations, and those guidelines are implemented as an immersive, interactive 3D flow visualization proof-of-concept application.

ISBN: 9798516963186Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

3D flow

An Empirical Evaluation of Visual Cues for 3D Flow Field Perception.
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300 $a 143 p.
500 $a Source: Dissertations Abstracts International, Volume: 83-01, Section: B.
500 $a Advisor: Butkiewicz, Thomas.
502 $a Thesis (Ph.D.)--University of New Hampshire, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a Three-dimensional vector fields are common datasets throughout the sciences. They often represent physical phenomena that are largely invisible to us in the real world, like wind patterns and ocean currents. Computer-aided visualization is a powerful tool that can represent data in any way we choose through digital graphics. Visualizing 3D vector fields is inherently difficult due to issues such as visual clutter, self-occlusion, and the difficulty of providing depth cues that adequately support the perception of flow direction in 3D space. Cutting planes are often used to overcome these issues by presenting slices of data that are more cognitively manageable. The existing literature provides many techniques for visualizing the flow through these cutting planes; however, there is a lack of empirical studies focused on the underlying perceptual cues that make popular techniques successful. The most valuable depth cue for the perception of other kinds of 3D data, notably 3D networks and 3D point clouds, is structure-from-motion (also called the Kinetic Depth Effect); another powerful depth cue is stereoscopic viewing, but none of these cues have been fully examined in the context of flow visualization. This dissertation presents a series of quantitative human factors studies that evaluate depth and direction cues in the context of cutting plane glyph designs for exploring and analyzing 3D flow fields. The results of the studies are distilled into a set of design guidelines to improve the effectiveness of 3D flow field visualizations, and those guidelines are implemented as an immersive, interactive 3D flow visualization proof-of-concept application.
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650 4 $a Hypotheses. $3 3560118
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650 4 $a Visualization. $3 586179
653 $a 3D flow
653 $a Data visualization
653 $a Depth cues
653 $a Flow visualization
653 $a Vector fields
653 $a Visual cues
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