Yasasi Abeysinghe, Bhanuka Mahanama, Gavindya Jayawardena, Mohan Sunkara, V. Ashok, S. Jayarathna
{"title":"用于分布式眼动追踪的凝视分析仪表板","authors":"Yasasi Abeysinghe, Bhanuka Mahanama, Gavindya Jayawardena, Mohan Sunkara, V. Ashok, S. Jayarathna","doi":"10.1109/IRI58017.2023.00031","DOIUrl":null,"url":null,"abstract":"Understanding the focus and visual scanning behavior of users during a collaborative activity in a distributed environment can be helpful in improving users’ engagement. Eye tracking measures can provide informative cues to understanding human visual search behavior. In this study, we present a distributed eye-tracking system with a gaze analytics dashboard. This system extracts eye movements from multiple participants utilizing common off-the-shelf eye trackers, generates real-time traditional positional gaze measures and advanced gaze measures such as ambient-focal coefficient $\\mathcal{K}$, and displays them in an interactive dashboard. We evaluate the proposed methodology by developing a gaze analytics dashboard and conducting a pilot study to (1) investigate the relationship between $\\mathcal{K}$ with collaborative behavior, and (2) compare it against the User Experience Questionnaire (UEQ) benchmark. Our results show that groups that spent more time had more ambient attention, and our dashboard has a higher overall impression compared to the UEQ benchmark.","PeriodicalId":290818,"journal":{"name":"2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Gaze Analytics Dashboard for Distributed Eye Tracking\",\"authors\":\"Yasasi Abeysinghe, Bhanuka Mahanama, Gavindya Jayawardena, Mohan Sunkara, V. Ashok, S. Jayarathna\",\"doi\":\"10.1109/IRI58017.2023.00031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Understanding the focus and visual scanning behavior of users during a collaborative activity in a distributed environment can be helpful in improving users’ engagement. Eye tracking measures can provide informative cues to understanding human visual search behavior. In this study, we present a distributed eye-tracking system with a gaze analytics dashboard. This system extracts eye movements from multiple participants utilizing common off-the-shelf eye trackers, generates real-time traditional positional gaze measures and advanced gaze measures such as ambient-focal coefficient $\\\\mathcal{K}$, and displays them in an interactive dashboard. We evaluate the proposed methodology by developing a gaze analytics dashboard and conducting a pilot study to (1) investigate the relationship between $\\\\mathcal{K}$ with collaborative behavior, and (2) compare it against the User Experience Questionnaire (UEQ) benchmark. Our results show that groups that spent more time had more ambient attention, and our dashboard has a higher overall impression compared to the UEQ benchmark.\",\"PeriodicalId\":290818,\"journal\":{\"name\":\"2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRI58017.2023.00031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRI58017.2023.00031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Gaze Analytics Dashboard for Distributed Eye Tracking
Understanding the focus and visual scanning behavior of users during a collaborative activity in a distributed environment can be helpful in improving users’ engagement. Eye tracking measures can provide informative cues to understanding human visual search behavior. In this study, we present a distributed eye-tracking system with a gaze analytics dashboard. This system extracts eye movements from multiple participants utilizing common off-the-shelf eye trackers, generates real-time traditional positional gaze measures and advanced gaze measures such as ambient-focal coefficient $\mathcal{K}$, and displays them in an interactive dashboard. We evaluate the proposed methodology by developing a gaze analytics dashboard and conducting a pilot study to (1) investigate the relationship between $\mathcal{K}$ with collaborative behavior, and (2) compare it against the User Experience Questionnaire (UEQ) benchmark. Our results show that groups that spent more time had more ambient attention, and our dashboard has a higher overall impression compared to the UEQ benchmark.