{"title":"OnMapGaze 和 GraphGazeD：用于在线地图服务中使用的制图背景视觉感知差异建模的凝视数据集和基于图形的度量标准","authors":"Dimitrios Liaskos, Vassilios Krassanakis","doi":"10.3390/mti8060049","DOIUrl":null,"url":null,"abstract":"In the present study, a new eye-tracking dataset (OnMapGaze) and a graph-based metric (GraphGazeD) for modeling visual perception differences are introduced. The dataset includes both experimental and analyzed gaze data collected during the observation of different cartographic backgrounds used in five online map services, including Google Maps, Wikimedia, Bing Maps, ESRI, and OSM, at three different zoom levels (12z, 14z, and 16z). The computation of the new metric is based on the utilization of aggregated gaze behavior data. Our dataset aims to serve as an objective ground truth for feeding artificial intelligence (AI) algorithms and developing computational models for predicting visual behavior during map reading. Both the OnMapGaze dataset and the source code for computing the GraphGazeD metric are freely distributed to the scientific community.","PeriodicalId":508555,"journal":{"name":"Multimodal Technologies and Interaction","volume":"40 23","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"OnMapGaze and GraphGazeD: A Gaze Dataset and a Graph-Based Metric for Modeling Visual Perception Differences in Cartographic Backgrounds Used in Online Map Services\",\"authors\":\"Dimitrios Liaskos, Vassilios Krassanakis\",\"doi\":\"10.3390/mti8060049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the present study, a new eye-tracking dataset (OnMapGaze) and a graph-based metric (GraphGazeD) for modeling visual perception differences are introduced. The dataset includes both experimental and analyzed gaze data collected during the observation of different cartographic backgrounds used in five online map services, including Google Maps, Wikimedia, Bing Maps, ESRI, and OSM, at three different zoom levels (12z, 14z, and 16z). The computation of the new metric is based on the utilization of aggregated gaze behavior data. Our dataset aims to serve as an objective ground truth for feeding artificial intelligence (AI) algorithms and developing computational models for predicting visual behavior during map reading. Both the OnMapGaze dataset and the source code for computing the GraphGazeD metric are freely distributed to the scientific community.\",\"PeriodicalId\":508555,\"journal\":{\"name\":\"Multimodal Technologies and Interaction\",\"volume\":\"40 23\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Multimodal Technologies and Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/mti8060049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimodal Technologies and Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/mti8060049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本研究引入了一个新的眼动跟踪数据集（OnMapGaze）和一个基于图形的指标（GraphGazeD）来模拟视觉感知差异。该数据集包括在观察谷歌地图、维基媒体、必应地图、ESRI 和 OSM 等五种在线地图服务中使用的不同制图背景时，在三种不同缩放级别（12z、14z 和 16z）下收集的实验和分析注视数据。新指标的计算基于聚合的注视行为数据。我们的数据集旨在为人工智能（AI）算法提供客观的基本事实，并为预测读图过程中的视觉行为开发计算模型。OnMapGaze 数据集和计算 GraphGazeD 指标的源代码都免费向科学界发布。
OnMapGaze and GraphGazeD: A Gaze Dataset and a Graph-Based Metric for Modeling Visual Perception Differences in Cartographic Backgrounds Used in Online Map Services
In the present study, a new eye-tracking dataset (OnMapGaze) and a graph-based metric (GraphGazeD) for modeling visual perception differences are introduced. The dataset includes both experimental and analyzed gaze data collected during the observation of different cartographic backgrounds used in five online map services, including Google Maps, Wikimedia, Bing Maps, ESRI, and OSM, at three different zoom levels (12z, 14z, and 16z). The computation of the new metric is based on the utilization of aggregated gaze behavior data. Our dataset aims to serve as an objective ground truth for feeding artificial intelligence (AI) algorithms and developing computational models for predicting visual behavior during map reading. Both the OnMapGaze dataset and the source code for computing the GraphGazeD metric are freely distributed to the scientific community.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
