Evaluating 2D Flow Visualization Using Eye Tracking

Ho, Hsin-Yang; Yeh, I-Cheng; Lai, Yu‐Chi; Lin, Wen‐Chieh; Cherng, Fu-Yin

doi:10.1111/cgf.12662

Cited by 11 publications

(5 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many researchers show how information is perceived through the eyes and how the gaze can be a rationale to evaluate the efficiency of visualization techniques [ 38 , 39 , 40 , 41 ]. Ho et al [ 42 ] presented the effectiveness of 2D flow visualization techniques using the eye-tracker to evaluate how every individual perceives the visualizations differently. Existing technologies utilize various visualizations to analyze the gaze.…”

Section: Related Workmentioning

confidence: 99%

Saliency-Based Gaze Visualization for Eye Movement Analysis

Yoo

Jeong

Kim

et al. 2021

Sensors

View full text Add to dashboard Cite

Gaze movement and visual stimuli have been utilized to analyze human visual attention intuitively. Gaze behavior studies mainly show statistical analyses of eye movements and human visual attention. During these analyses, eye movement data and the saliency map are presented to the analysts as separate views or merged views. However, the analysts become frustrated when they need to memorize all of the separate views or when the eye movements obscure the saliency map in the merged views. Therefore, it is not easy to analyze how visual stimuli affect gaze movements since existing techniques focus excessively on the eye movement data. In this paper, we propose a novel visualization technique for analyzing gaze behavior using saliency features as visual clues to express the visual attention of an observer. The visual clues that represent visual attention are analyzed to reveal which saliency features are prominent for the visual stimulus analysis. We visualize the gaze data with the saliency features to interpret the visual attention. We analyze the gaze behavior with the proposed visualization to evaluate that our approach to embedding saliency features within the visualization supports us to understand the visual attention of an observer.

show abstract

Section: Related Workmentioning

confidence: 99%

Saliency-Based Gaze Visualization for Eye Movement Analysis

Yoo

Jeong

Kim

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Results are based on control measures such as the error rate and/or the time needed to perform the task [PW13]. Such measures can be complemented with additional data such as eye tracking [HYL∗15]. Earlier studies focus mainly on static visualization techniques [LCE∗12, LKJ∗05].…”

Section: Related Workmentioning

confidence: 99%

Feature Driven Combination of Animated Vector Field Visualizations

Lobo

Telea

Hurter

2020

Computer Graphics Forum

View full text Add to dashboard Cite

Animated visualizations are one of the methods for finding and understanding complex structures of time‐dependent vector fields. Many visualization designs can be used to this end, such as streamlines, vector glyphs, and image‐based techniques. While all such designs can depict any vector field, their effectiveness in highlighting particular field aspects has not been fully explored. To fill this gap, we compare three animated vector field visualization techniques, OLIC, IBFV, and particles, for a critical point detection‐and‐classification task through a user study. Our results show that the effectiveness of the studied techniques depends on the nature of the critical points. We use these results to design a new flow visualization technique that combines all studied techniques in a single view by locally using the most effective technique for the patterns present in the flow data at that location. A second user study shows that our technique is more efficient and less error prone than the three other techniques used individually for the critical point detection task.

show abstract

“…Hsin-Yang Ho, et al [35] conducted an eye tracking experiment to explore the influences of five different two-dimensional flow visualization methods on the visual perception of the user. They obtained several new findings that were not observed in previous studies.…”

Section: Related Workmentioning

confidence: 99%

Using Eye Tracking to Evaluate the Usability of Flow Maps

Dong

Wang

Chen

et al. 2018

IJGI

View full text Add to dashboard Cite

Flow maps allow users to perceive not only the location where interactions take place, but also the direction and volume of events. Previous studies have proposed numerous methods to produce flow maps. However, how to evaluate the usability of flow maps has not been well documented. In this study, we combined eye-tracking and questionnaire methods to evaluate the usability of flow maps through comparisons between (a) straight lines and curves and (b) line thicknesses and color gradients. The results show that curved flows are more effective than straight flows. Maps with curved flows have more correct answers, fixations, and percentages of fixations in areas of interest. Furthermore, we find that the curved flows require longer finish times but exhibit smaller times to first fixation than straight flows. In addition, we find that using color gradients to indicate the flow volume is significantly more effective than the application of different line thicknesses, which is mainly reflected by the presence of more correct answers in the color-gradient group. These empirical studies could help improve the usability of flow maps employed to visualize geo-data.

show abstract

Evaluating 2D Flow Visualization Using Eye Tracking

Cited by 11 publications

References 29 publications

Saliency-Based Gaze Visualization for Eye Movement Analysis

Saliency-Based Gaze Visualization for Eye Movement Analysis

Feature Driven Combination of Animated Vector Field Visualizations

Using Eye Tracking to Evaluate the Usability of Flow Maps

Contact Info

Product

Resources

About