Gazed and Confused

D’Angelo, Sarah; Gergle, Darren

doi:10.1145/2858036.2858499

Cited by 67 publications

(12 citation statements)

References 19 publications

(10 reference statements)

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“…Those studies suggest that the design of gaze visualisations affects performance, coordination, searching behaviour, and perceived utility, although certain visualisations can overwhelm users by the excessive amount of visual information shown (D'Angelo and Gergle, 2018) (Zhang et al, 2017) (Li et al, 2016). For instance, a continuous gaze stream (D'Angelo and Gergle, 2016) or cumulative gaze heatmap (D'Angelo and Gergle, 2018) are both considered distracting, while with a gaze indicator on a 2D display users often need to constantly identify the gaze owner (Zhang et al, 2017).…”

Section: Visual Interfaces Of Gaze Cues In Collaborationmentioning

confidence: 99%

Eye See What You See: Exploring How Bi-Directional Augmented Reality Gaze Visualisation Influences Co-Located Symmetric Collaboration

Jing

May

Lee

et al. 2021

Front. Virtual Real.

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Gaze is one of the predominant communication cues and can provide valuable implicit information such as intention or focus when performing collaborative tasks. However, little research has been done on how virtual gaze cues combining spatial and temporal characteristics impact real-life physical tasks during face to face collaboration. In this study, we explore the effect of showing joint gaze interaction in an Augmented Reality (AR) interface by evaluating three bi-directional collaborative (BDC) gaze visualisations with three levels of gaze behaviours. Using three independent tasks, we found that all bi-directional collaborative BDC visualisations are rated significantly better at representing joint attention and user intention compared to a non-collaborative (NC) condition, and hence are considered more engaging. The Laser Eye condition, spatially embodied with gaze direction, is perceived significantly more effective as it encourages mutual gaze awareness with a relatively low mental effort in a less constrained workspace. In addition, by offering additional virtual representation that compensates for verbal descriptions and hand pointing, BDC gaze visualisations can encourage more conscious use of gaze cues coupled with deictic references during co-located symmetric collaboration. We provide a summary of the lessons learned, limitations of the study, and directions for future research.

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Section: Visual Interfaces Of Gaze Cues In Collaborationmentioning

confidence: 99%

Eye See What You See: Exploring How Bi-Directional Augmented Reality Gaze Visualisation Influences Co-Located Symmetric Collaboration

Jing

May

Lee

et al. 2021

Front. Virtual Real.

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show abstract

“…We performed normality tests on the gaze points of each target fixation, separately in the x-and y-directions (D'Agostino and Pearson's test as implemented by Python's SciPy package [7,20] with a significance level of p < .01). They showed that on average gaze points are normally distributed in the x-direction for 71% of the fixations, and in the y-direction for 74%.…”

Section: Data Loss and Distribution Of Gaze Pointsmentioning

confidence: 99%

“…[13,38]) could adapt their font size and word spacing for better recognition of fixations during reading. Visualizing tracking quality to the end user could be useful, for example in remote collaborative settings where information about collaborators' gaze can be a useful communication tool, but a noisy signal can be confusing [7].…”

mentioning

confidence: 99%

Toward Everyday Gaze Input

Feit

Williams

Toledo

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

152

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For eye tracking to become a ubiquitous part of our everyday interaction with computers, we first need to understand its limitations outside rigorously controlled labs, and develop robust applications that can be used by a broad range of users and in various environments. Toward this end, we collected eye tracking data from 80 people in a calibration-style task, using two different trackers in two lighting conditions. We found that accuracy and precision can vary between users and targets more than six-fold, and report on differences between lighting, trackers, and screen regions. We show how such data can be used to determine appropriate target sizes and to optimize the parameters of commonly used filters. We conclude with design recommendations and examples how our findings and methodology can inform the design of erroraware adaptive applications.

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“…However, studies on shared gaze visualizations for various applications have found that the introduction of shared gaze awareness can be disruptive, often being referred to as 'distracting' and 'confusing' [6,16]. We hypothesise that this is caused by two primary problems with gaze visualization for digital interfaces.…”

Section: Introductionmentioning

confidence: 91%

“…Gaze information can be 'noisy' due to the jittery movements and the way the eyes work (fixation-saccade-fixation cycle), and this is reflected in the representations. Gaze data is difficult to interpret and often misunderstood [6], as even trained professionals in eyetracking evaluations make use of a range of gaze visualizations to make sense of the same collected data. Further, as gaze is fast-moving and never entirely still, any real-time visualization overlaid on a user interface adds a highly distracting element that may interfere with the viewer's own thought process.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Real-Time Gaze Representations to Infer Intentions in Competitive Turn-Based Strategy Games

Newn

Velloso

Allison

et al. 2017

Proceedings of the Annual Symposium on Computer-Human Interaction in Play

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In this paper, we investigate nine different visual representations of gaze in a competitive digital game setting. We evaluate the ability of spectators to infer a player's intentions in the game for each visual representation. Our results show that spectators have a remarkable ability to infer intent accurately using all nine visualizations, but that visualizations with certain characteristics were more comprehensible and more readily revealed the player's intent. The real-time Heatmap visualization was the most highly preferred by participants and the most effective in revealing intent, due to its ability to balance real-time gaze information with a persistent summary of recent gaze behaviour. Our findings show that eye-tracking visualization can enable playful interactions in competitive games based on players' ability to interpret opponents' attention and intention through gaze information.

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Gazed and Confused

Cited by 67 publications

References 19 publications

Eye See What You See: Exploring How Bi-Directional Augmented Reality Gaze Visualisation Influences Co-Located Symmetric Collaboration

Eye See What You See: Exploring How Bi-Directional Augmented Reality Gaze Visualisation Influences Co-Located Symmetric Collaboration

Toward Everyday Gaze Input

Evaluating Real-Time Gaze Representations to Infer Intentions in Competitive Turn-Based Strategy Games

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