Michael Burch, Günter Wallner, Veerle Fürst, Teodor-Cristian Lungu, Daan Boelhouwers, Dhiksha Rajasekaran, Richard Farla, Sander van Heesch
{"title":"Linked and Coordinated Visual Analysis of Eye Movement Data","authors":"Michael Burch, Günter Wallner, Veerle Fürst, Teodor-Cristian Lungu, Daan Boelhouwers, Dhiksha Rajasekaran, Richard Farla, Sander van Heesch","doi":"10.1145/3517031.3531163","DOIUrl":null,"url":null,"abstract":"Eye movement data can be used for a variety of research in marketing, advertisement, and other design-related industries to gain interesting insights into customer preferences. However, interpreting such data can be a challenging task due to its spatio-temporal complexity. In this paper we describe a web-based tool that has been developed to provide various visualizations for interpreting eye movement data of static stimuli. The tool provides several techniques to visualize and analyze eye movement data. These visualizations are interactive and linked in a coordinated way to help gain more insights. Overall, this paper illustrates the features and functionality offered by the tool by using data recorded from transport map readers in a previously conducted experiment as use case. Furthermore, the paper discusses limitations of the tool and possible future developments.","PeriodicalId":339393,"journal":{"name":"2022 Symposium on Eye Tracking Research and Applications","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Symposium on Eye Tracking Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3517031.3531163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Eye movement data can be used for a variety of research in marketing, advertisement, and other design-related industries to gain interesting insights into customer preferences. However, interpreting such data can be a challenging task due to its spatio-temporal complexity. In this paper we describe a web-based tool that has been developed to provide various visualizations for interpreting eye movement data of static stimuli. The tool provides several techniques to visualize and analyze eye movement data. These visualizations are interactive and linked in a coordinated way to help gain more insights. Overall, this paper illustrates the features and functionality offered by the tool by using data recorded from transport map readers in a previously conducted experiment as use case. Furthermore, the paper discusses limitations of the tool and possible future developments.