Gazing at Games: An Introduction to Eye Tracking Control

Sundstedt, Veronica

doi:10.2200/s00395ed1v01y201111cgr014

Cited by 25 publications

(19 citation statements)

References 103 publications

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“…It highlights the frequently fixated regions by the user. The areas with a high number of fixations and/or fixations duration are called hotspots [45]. Apart from the visual aspects, in such methods, comparing two scan paths remains difficult, hence the use of another graphical method.…”

Section: State Of the Artmentioning

confidence: 99%

Local Sequence Alignment for Scan Path Similarity Assessment

Khedher¹,

Jraidi²,

Frasson³

2018

IJIET

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Abstract-It has long been shown that there is a close relationship between eye movement, human cognition and brain activity. The present work seeks to explore this relationship by investigating the students' saccadic eye movement sequences in a problem solving task. We aim to assess students' reasoning process in a clinical problem solving task using students' visual trajectories. We use students' scan path, followed while resolving medical cases, and a local sequence alignment algorithm, to evaluate their analytical reasoning during medical case resolution. An experimental protocol was conducted with 15 participants. Eye movements were recorded while they were interacting with our learning environment. The proposed approach, based on gaze data, can be reliably applied to eye movement sequence comparison. Our findings have implications for improving novice clinicians' reasoning abilities in particular and ultimately enhancing learning outcomes.Index Terms-Cognitive tasks, eye movements, local sequence alignment, medical reasoning, scan path similarity.

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Section: State Of the Artmentioning

confidence: 99%

Local Sequence Alignment for Scan Path Similarity Assessment

Khedher¹,

Jraidi²,

Frasson³

2018

IJIET

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“…These have been pioneered both inside academia and out, for groups of individuals with diseases like amyotrophic lateral sclerosis (ALS), a peripheral motor-neuron disease paralyzing the body, while leaving eye movements in tact. These studies most often involve the movement of a cursor, wheelchair, and accessories via the point of gaze, while defining a variety of mouse-click paradigms, including blinks and others, as well as the use of gaze location to control computer graphical menus, zooming of windows, or context-sensitive presentation of information (Jacob, 1990(Jacob, , 1991(Jacob, , 1993aJakob, 1998;Zhai et al, 1999;Tanriverdi and Jacob, 2000;Ashmore et al, 2005;Laqua et al, 2007;Liu et al, 2012;Sundstedt, 2012;Hild et al, 2013;Wankhede et al, 2013). These paradigms have been extended to improve upon human control of robots (Carlson and Demiris, 2009), as well as humans controlling swarms (Couture-Beil et al, 2010;Monajjemi et al, 2013).…”

Section: Gaze Control: Computer Robot and Swarm Controlmentioning

confidence: 99%

Human Strategies for Multitasking, Search, and Control Improved via Real-Time Memory Aid for Gaze Location

Taylor

Bilgrien

et al. 2015

Front. ICT

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Objective: We aimed to elucidate how our domain-general cuing algorithm improved multitasking performance and changed behavioral strategies in human operators.Background: Though many gaze-control systems have been designed, previous realtime gaze-aware assistance systems were not both successful and domain-general. It is largely unknown what constitutes optimal search efficiency using the eyes, or ideal control using the mouse. It is unclear what the best coordinating strategies are between these two modalities. Our previously developed closed-loop multitasking aid drastically improved multitasking performance, though the behavioral mechanisms through which it acted were unknown. Methods:We performed in-depth analyses and generated novel eye tracking and mouse movement measures, to explore the complex effects of our helpful system on gaze and motor behavior.Results: Our overlay cuing algorithm improved control efficiency and reduced wellknown biases in search patterns. This system also reduced micromanaging behavior, with humans rationally relying more on imperfect automation in experimental assistance cue conditions. We showed that mouse and gaze were more independently specialized in the helpful cuing condition than in control conditions. Specifically, with our aid, the gaze performed more global movement, and the mouse performed more local clustered movement. Further, the gaze shifted toward search over processing with the helpful cuing system. We also illustrated a relationship between the mouse and the gaze, such that in these studies, "the hand was quicker than the eye." Conclusion:Overall, results suggested that our cuing system improved performance and reduced short-term working memory load on humans by delegating it to the computer in real time. Further, it reduced the number of required repeated decisions by an estimate of about one per second. It also enabled the gaze to specialize for improved visual search behavior, and the mouse to specialize for improved control.

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“…The eye muscles enable fast gaze shifting to orient the eye such that the object of interest is projected onto the fovea. There are five types of eye movements: saccades -fast movements used to reposition the fovea, smooth pursuits -active when eyes track moving targets, vergence -used for depth perception to focus the pair of eyes over a target, vestibular ocular reflex -used to compensate head movement, and optokinetic reflex -used to account for the motion of the visual field [Duc07,Sun12].…”

Section: Human Eye Movement and Visual Fixationmentioning

confidence: 99%

“…In this work we demonstrate the use of eye tracker as an intuitive and very fast controller in a computer game (see Section 8.2 and [Sun12]). …”

Section: Gaze Tracking In Computer Graphicsmentioning

confidence: 99%

Gaze‐driven Object Tracking for Real Time Rendering

Mantiuk

Bazyluk

Mantiuk

2013

Computer Graphics Forum

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To efficiently deploy eye-tracking within 3D graphics applications, we present a new probabilistic method that predicts the patterns of user's eye fixations in animated 3D scenes from noisy eye-tracker data. The proposed method utilises both the eye-tracker data and the known information about the 3D scene to improve the accuracy, robustness and stability. Eye-tracking can thus be used, for example, to induce focal cues via gaze-contingent depth-of-field rendering, add intuitive controls to a video game, and create a highly reliable scene-aware saliency model. The computed probabilities rely on the consistency of the gaze scan-paths to the position and velocity of a moving or stationary target. The temporal characteristic of eye fixations is imposed by a Hidden Markov model, which steers the solution towards the most probable fixation patterns. The derivation of the algorithm is driven by the data from two eye-tracking experiments: the first experiment provides actual eye-tracker readings and the position of the target to be tracked. The second experiment is used to derive a JND-scaled (Just Noticeable Difference) quality metric that quantifies the perceived loss of quality due to the errors of the tracking algorithm. Data from both experiments are used to justify design choices, and to calibrate and validate the tracking algorithms. This novel method outperforms commonly used fixation algorithms and is able to track objects smaller then the nominal error of an eye-tracker.

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Gazing at Games: An Introduction to Eye Tracking Control

Cited by 25 publications

References 103 publications

Local Sequence Alignment for Scan Path Similarity Assessment

Local Sequence Alignment for Scan Path Similarity Assessment

Human Strategies for Multitasking, Search, and Control Improved via Real-Time Memory Aid for Gaze Location

Gaze‐driven Object Tracking for Real Time Rendering

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