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Evaluating 2D Flow Visualization Using Eye Tracking
Author(s) -
Ho HsinYang,
Yeh ICheng,
Lai YuChi,
Lin WenChieh,
Cherng FuYin
Publication year - 2015
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12662
Subject(s) - visualization , computer science , eye tracking , feature (linguistics) , visual analytics , computer vision , perception , scientific visualization , artificial intelligence , identification (biology) , perspective (graphical) , data visualization , flow visualization , information visualization , field (mathematics) , flow (mathematics) , human–computer interaction , mathematics , philosophy , linguistics , botany , geometry , neuroscience , pure mathematics , biology
Flow visualization is recognized as an essential tool for many scientific research fields and different visualization approaches are proposed. Several studies are also conducted to evaluate their effectiveness but these studies rarely examine the performance from the perspective of visual perception. In this paper, we aim at exploring how users’ visual perception is influenced by different 2D flow visualization methods. An eye tracker is used to analyze users’ visual behaviors when they perform the free viewing, advection prediction, flow feature detection, and flow feature identification tasks on the flow field images generated by different visualizations methods. We evaluate the illustration capability of five representative visualization algorithms. Our results show that the eye‐tracking‐based evaluation provides more insights to quantitatively analyze the effectiveness of these visualization methods.