Mieke Sarah Slim, Margaret Kandel, Anthony Yacovone, Jesse Snedeker
{"title":"Webcams as Windows to the Mind? A Direct Comparison Between In-Lab and Web-Based Eye-Tracking Methods.","authors":"Mieke Sarah Slim, Margaret Kandel, Anthony Yacovone, Jesse Snedeker","doi":"10.1162/opmi_a_00171","DOIUrl":null,"url":null,"abstract":"<p><p>There is a growing interest in the use of webcams to conduct eye-tracking experiments over the internet. We assessed the performance of two webcam-based eye-tracking techniques for behavioral research: manual annotation of webcam videos (<i>manual eye-tracking</i>) and the automated WebGazer eye-tracking algorithm. We compared these methods to a traditional infrared eye-tracker and assessed their performance in both lab and web-based settings. In both lab and web experiments, participants completed the same battery of five tasks, selected to trigger effects of various sizes: two visual fixation tasks and three visual world tasks testing real-time (psycholinguistic) processing effects. In the lab experiment, we simultaneously collected infrared eye-tracking, manual eye-tracking, and WebGazer data; in the web experiment, we simultaneously collected manual eye-tracking and WebGazer data. We found that the two webcam-based methods are suited to capture different types of eye-movement patterns. Manual eye-tracking, similar to infrared eye-tracking, detected both large and small effects. WebGazer, however, showed less accuracy in detecting short, subtle effects. There was no notable effect of setting for either method. We discuss the trade-offs researchers face when choosing eye-tracking methods and offer advice for conducting eye-tracking experiments over the internet.</p>","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"8 ","pages":"1369-1424"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11627531/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Mind","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1162/opmi_a_00171","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
There is a growing interest in the use of webcams to conduct eye-tracking experiments over the internet. We assessed the performance of two webcam-based eye-tracking techniques for behavioral research: manual annotation of webcam videos (manual eye-tracking) and the automated WebGazer eye-tracking algorithm. We compared these methods to a traditional infrared eye-tracker and assessed their performance in both lab and web-based settings. In both lab and web experiments, participants completed the same battery of five tasks, selected to trigger effects of various sizes: two visual fixation tasks and three visual world tasks testing real-time (psycholinguistic) processing effects. In the lab experiment, we simultaneously collected infrared eye-tracking, manual eye-tracking, and WebGazer data; in the web experiment, we simultaneously collected manual eye-tracking and WebGazer data. We found that the two webcam-based methods are suited to capture different types of eye-movement patterns. Manual eye-tracking, similar to infrared eye-tracking, detected both large and small effects. WebGazer, however, showed less accuracy in detecting short, subtle effects. There was no notable effect of setting for either method. We discuss the trade-offs researchers face when choosing eye-tracking methods and offer advice for conducting eye-tracking experiments over the internet.