Lack of accuracy in eye-tracking data can be critical. If the point of gaze is not recorded accurately and reliably, the information obtained or action executed might be different from what the user intended. This study reports trackability, accuracy, and precision as indicators of eye-tracking data quality as measured at various head positions and light conditions for a sample of participants from three different ethnic groups. It was found that accuracy and precision for Asian participants was worse than that for African and Caucasian participants. No significant differences were found between the latter two ethnic groups. Operating distance had the largest effect on data quality, since it affected all indicators for all ethnic groups. Illumination had no significant effect on accuracy or precision, but the accuracy achieved by African and Caucasian participants was better when the stimulus was presented on a dark background. Large gaze angles proved to be detrimental for trackability for African participants, while accuracy and precision were also affected adversely by larger gaze angles for two of the ethnicities.
In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section “An empirically based minimal reporting guideline”).
In a video-based eye tracker, the normalized pupil-glint vector changes as the eyes move. Using an appropriate model, the pupil-glint vector can be mapped to gaze coordinates. Using a simple hardware configuration with one camera and one infrared source, several mapping functions – some from literature and some derived here – were compared with one another with respect to the accuracy that could be achieved. The study served to confirm the results of a previous study with another data set and to expand on the possibilities that are considered from the previous study. The data of various participants was examined for trends which led to derivation of a mapping model that proved to be more accurate than all but one model from literature. It was also shown that the best calibration configuration for this hardware setup is one that contains fourteen targets while taking about 20 seconds for the procedure to be completed.
For evaluating whether an eye-tracker is suitable for measuring microsaccades, Poletti & Rucci (2016) propose that a measure called 'resolution' could be better than the more established root-mean-square of the sample-to-sample distances (RMS-S2S). Many open questions exist around the resolution measure, however. Resolution needs to be calculated using data from an artificial eye that can be turned in very small steps. Furthermore, resolution has an unclear and uninvestigated relationship to the RMS-S2S and STD (standard deviation) measures of precision (Holmqvist & Andersson, 2017, p. 159-190), and there is another metric by the same name (Clarke, Ditterich, Drüen, Schönfeld, and Steineke 2002), which instead quantifies the errors of amplitude measurements. In this paper, we present a mechanism, the Stepperbox, for rotating artificial eyes in arbitrary angles from 1 ′ (arcmin) and upward. We then use the Stepperbox to find the minimum reliably detectable rotations in 11 video-based eye-trackers (VOGs) and the Dual Purkinje Imaging (DPI) tracker. We find that resolution correlates significantly with RMS-S2S and, to a lesser extent, with STD. In addition, we find that although most eye-trackers can detect some small rotations of an artificial eye, the rotations of amplitudes up to 2 ∘ are frequently erroneously measured by video-based eye-trackers. We show evidence that the corneal reflection (CR) feature of these eye-trackers is a major cause of erroneous measurements of small rotations of artificial eyes. Our data strengthen the existing body of evidence that video-based eye-trackers produce errors that may require that we reconsider some results from research on reading, microsaccades, and vergence, where the amplitude of small eye movements have been measured with past or current video-based eye-trackers. In contrast, the DPI reports correct rotation amplitudes down to 1 ′ .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.