Specifying of Requirements for Spatio-Temporal Data in Map by Eye-Tracking and Space-Time-Cube

被引:17
|
作者
Popelka, Stanislav [1 ]
Vozenilek, Vit [1 ]
机构
[1] Palacky Univ, CR-77147 Olomouc, Czech Republic
来源
INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2012) | 2013年 / 8768卷
关键词
Space-Time-Cube; Spatio-Temporal data; Eye-tracking; Eye-movement; Visualization;
D O I
10.1117/12.2011438
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
One of the most objective methods of map use evaluation (in terms of reading, analysis and interpretation. is an analysis of eye movements of map reader, known as eye-tracking method. GazePlots and HeatMaps as the most commonly used visualization methods of eye-tracking data cannot effectively express the change of time. The authors introduce a Space-Time-Cube for spatio-temporal visualization. It displays the map at the base of the cube (axes X and Y) while Z axis is used to represent time. Spatial and temporal components of a map are shown together, and relationship between space and time can be revealed. During the authors' research, the user interaction over the map legend of agriculture of the Czech Republic school maps was tested. Space-Time-Cube displayed both components (spatial and temporal) together and allowed easy visual analysis of four respondents' (map readers') work with a map. Using Space-Time-Cube for visual analysis provides satisfactory results, although this form of visualization is not widespread and for someone it may seem complex and confusing.
引用
收藏
页数:5
相关论文
共 50 条
  • [1] Visual Exploration of Eye Movement Data Using the Space-Time-Cube
    Li, Xia
    Coltekin, Arzu
    Kraak, Menno-Jan
    GEOGRAPHIC INFORMATION SCIENCE, 2010, 6292 : 295 - +
  • [2] A Spatio-Temporal Extension to the Map Cube Operator
    Alzate, Juan C.
    Moreno, Francisco J.
    Echeverri, Jaime
    NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2012), VOLS A AND B, 2012, 1479 : 2310 - 2314
  • [3] SPATIO-TEMPORAL COMBINATION OF SALIENCY MAPS AND EYE-TRACKING ASSESSMENT OF DIFFERENT STRATEGIES
    Chamaret, C.
    Chevet, J. C.
    Le Meur, O.
    2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, 2010, : 1077 - 1080
  • [4] A user study of visualisations of spatio-temporal eye tracking data
    Claus, Marcel
    Hermens, Frouke
    Bromuri, Stefano
    JOURNAL OF VISUALIZATION, 2025, 28 (01) : 153 - 169
  • [5] Modeling spatio-temporal patterns in intensive binary time series eye-tracking data using Generalized Additive Mixed Models
    Brown-Schmidt, Sarah
    Cho, Sun-Joo
    Fenn, Kimberly M.
    Trude, Alison M.
    BRAIN RESEARCH, 2025, 1854
  • [6] Static visualization of temporal eye-tracking data
    Räïhä, KJ
    Aula, A
    Majaranta, P
    Rantala, H
    Koivunen, K
    HUMAN-COMPUTER INTERACTION - INTERACT 2005, PROCEEDINGS, 2005, 3585 : 946 - 949
  • [7] Exploring Eye Movement Patterns on Cartographic Animations Using Projections of a Space-Time-Cube
    Nossum, Alexander Salveson
    CARTOGRAPHIC JOURNAL, 2014, 51 (03): : 249 - 256
  • [8] Tracking as motion boundary detection in spatio-temporal space
    Feghali, R
    Mitiche, A
    Mansouri, AR
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON IMAGING SCIENCE, SYSTEMS AND TECHNOLOGY, VOLS I AND II, 2001, : 600 - 604
  • [9] Real Time Eye Tracking using Kalman Extended Spatio-Temporal Context Learning
    Munir, Farzeen
    Minhas, Fayyaz ul Amir Afsar
    Jalil, Abdul
    Jeon, Moongu
    SECOND INTERNATIONAL WORKSHOP ON PATTERN RECOGNITION, 2017, 10443
  • [10] Computational Methods for Continuous Eye-Tracking Perimetry Based on Spatio-Temporal Integration and a Deep Recurrent Neural Network
    Grillini, Alessandro
    Hernandez-Garcia, Alex
    Renken, Remco J.
    Demaria, Giorgia
    Cornelissen, Frans W.
    FRONTIERS IN NEUROSCIENCE, 2021, 15