1. Gazealytics: A Unified and Flexible Visual Toolkit for Exploratory and Comparative Gaze Analysis
- Author
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Kun-Ting Chen, Arnaud Prouzeau, Joshua Langmead, Ryan T Whitelock-Jones, Lee Lawrence, Tim Dwyer, Christophe Hurter, Daniel Weiskopf, Sarah Goodwin, University of South Australia [Adelaide], Popular interaction with 3d content (Potioc), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Monash University [Melbourne], Monash university, Ecole Nationale de l'Aviation Civile (ENAC), Visualization Research Center [Stuttgart] (VISUS), and Universität Stuttgart [Stuttgart]
- Subjects
FOS: Computer and information sciences ,Eye tracking ,time window of interest ,matrix-based overview ,Computer Science - Human-Computer Interaction ,[INFO]Computer Science [cs] ,visual analytics ,area of interest ,group-level visualisation ,Human-Computer Interaction (cs.HC) - Abstract
International audience; We present a novel, web-based visual eye-tracking analytics tool called Gazealytics. Our open-source toolkit features a unified combination of gaze analytics features that support flexible exploratory analysis, along with annotation of areas of interest (AOI) and filter options based on multiple criteria to visually analyse eye tracking data across time and space. Gazealytics features coordinated views unifying spatiotemporal exploration of fixations and scanpaths for various analytical tasks. A novel matrix representation allows analysis of relationships between such spatial or temporal features. Data can be grouped across samples, user-defined AOIs or time windows of interest (TWIs) to support aggregate or filtered analysis of gaze activity. This approach exceeds the capabilities of existing systems by supporting flexible comparison between and within subjects, hypothesis generation, data analysis and communication of insights. We demonstrate in a walkthrough that Gazealytics supports multiple types of eye tracking datasets and analytical tasks.
- Published
- 2023
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