Measuring the Spatial Noise of a Low-Cost Eye Tracker to Enhance Fixation Detection

Ooms, Kristien; Krassanakis, Vassilios

doi:10.3390/jimaging4080096

Cited by 28 publications

(19 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These two features are also very important for classifier models. Coincidentally, they can be determined fairly robustly from relative two-dimensional gaze positions alone, and are therefore easily obtainable with low-cost eye tracking systems (see Ooms & Krassanakis, 2018, for a state-ofthe-art assessment of low-cost eye tracking) or webcam-based eye tracking (e.g., Webgazer by Papoutsaki et al, 2016).…”

Section: Resultsmentioning

confidence: 99%

Predicting artificial visual field losses: A gaze-based inference study

et al. 2019

View full text Add to dashboard Cite

Visual field defects are a worldwide concern, and the proportion of the population experiencing vision loss is ever increasing. Macular degeneration and glaucoma are among the four leading causes of permanent vision loss. Identifying and characterizing visual field losses from gaze alone could prove crucial in the future for screening tests, rehabilitation therapies, and monitoring. In this experiment, 54 participants took part in a free-viewing task of visual scenes while experiencing artificial scotomas (central and peripheral) of varying radii in a gaze-contingent paradigm. We studied the importance of a set of gaze features as predictors to best differentiate between artificial scotoma conditions. Linear mixed models were utilized to measure differences between scotoma conditions. Correlation and factorial analyses revealed redundancies in our data. Finally, hidden Markov models and recurrent neural networks were implemented as classifiers in order to measure the predictive usefulness of gaze features. The results show separate saccade direction biases depending on scotoma type. We demonstrate that the saccade relative angle, amplitude, and peak velocity of saccades are the best features on the basis of which to distinguish between artificial scotomas in a free-viewing task. Finally, we discuss the usefulness of our protocol and analyses as a gaze-feature identifier tool that discriminates between artificial scotomas of different types and sizes.

show abstract

Section: Resultsmentioning

confidence: 99%

Predicting artificial visual field losses: A gaze-based inference study

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Finally, although that recent experimental studies validate that low cost eye tracking devices can be used for scientific purposes (see e.g., [66][67][68]), the raw gaze data, which are distributed through the EyeTrackUAV dataset, have been collected with one of the most precise and accurate eye trackers, serving as a robust ground truth for future studies.…”

Section: Discussionmentioning

confidence: 99%

Monitoring Human Visual Behavior during the Observation of Unmanned Aerial Vehicles (UAVs) Videos

Krassanakis

Silva

Ricordel

2018

Drones

Self Cite

View full text Add to dashboard Cite

The present article describes an experimental study towards the examination of human visual behavior during the observation of unmanned aerial vehicles (UAVs) videos. Experimental performance is based on the collection and the quantitative & qualitative analysis of eye tracking data. The results highlight that UAV flight altitude serves as a dominant specification that affects the visual attention process, while the presence of sky in the video background seems to be the less affecting factor in this procedure. Additionally, the main surrounding environment, the main size of the observed object as well as the main perceived angle between UAV’s flight plain and ground appear to have an equivalent influence in observers’ visual reaction during the exploration of such stimuli. Moreover, the provided heatmap visualizations indicate the most salient locations in the used UAVs videos. All produced data (raw gaze data, fixation and saccade events, and heatmap visualizations) are freely distributed to the scientific community as a new dataset (EyeTrackUAV) that can be served as an objective ground truth in future studies.

show abstract

“…However, in memorizing the route on the basis of animation, the most crucial variable is location because the object moves from the starting point to the destination point. The eye-tracking used in cartographic studies often uses devices with 60-120 Hz sampling frequency and 0.5 • of spatial accuracy and were validated as suitable for scientific research [53,54].…”

Section: Related Researchmentioning

confidence: 99%

Effectiveness of Memorizing an Animated Route—Comparing Satellite and Road Map Differences in the Eye-Tracking Study

Cybulski¹

2021

IJGI

View full text Add to dashboard Cite

There is no consensus on the importance of satellite images in the process of memorizing a route from a map image, especially if the route is displayed on the Internet using dynamic (animated) cartographic visualization. In modern dynamic maps built with JavaScript APIs, background layers can be easily altered by map users. The animation attracts people’s attention better than static images, but it causes some perceptual problems. This study examined the influence of the number of turns on the effectiveness (correctness) and efficiency of memorizing the animated route on different cartographic backgrounds. The routes of three difficulty levels, based on satellite and road background, were compared. The results show that the satellite background was not a significant factor influencing the efficiency and effectiveness of route memorizing. Recordings of the eye movement confirmed this. The study reveals that there were intergroup differences in participants' visual behavior. Participants who described their spatial abilities as “very good” performed better (in terms of effectiveness and efficiency) in route memorizing tasks. For future research, there is a need to study route variability and its impact on participants’ performance. Moreover, future studies should involve differences in route visualization (e.g., without and with ephemeral or permanent trail).

show abstract

Measuring the Spatial Noise of a Low-Cost Eye Tracker to Enhance Fixation Detection

Cited by 28 publications

References 58 publications

Predicting artificial visual field losses: A gaze-based inference study

Predicting artificial visual field losses: A gaze-based inference study

Monitoring Human Visual Behavior during the Observation of Unmanned Aerial Vehicles (UAVs) Videos

Effectiveness of Memorizing an Animated Route—Comparing Satellite and Road Map Differences in the Eye-Tracking Study

Contact Info

Product

Resources

About