Primary supervisorSarah Goodwin
- Maxime Cordeil (UQ, Brisbane)
- Arnaud Prouzeau (Indra, France)
- Kun-Ting Chen (Stuttgart, Germany)
Our research explores the use of data visualisation to visually analyse complex eye tracking data and have spent the last few years developing open-source eye tracking analysis software along side feedback from those who use eye tracking in their work.
Eye tracking is widely used in various domains. Eye-tracking data consists of a record over time of eye position relative to the scene being viewed. Important features relate to fixations (steady gaze on a particular location for some period of time) and saccades (quick eye movements between locations). Most eye tracking occurs in controlled studies in laboratories that require external sensors to track gaze. However, with the growing development of wearable eye trackers (e.g. Tobii Pro), it is now possible to perform ‘in the wild’ studies (i.e. in the participant’s natural environment) by having participants wear eye tracking glasses. These ‘in the wild’ studies tend to produce large amounts of less controlled data. Current eye-tracking analysis software provide limited solutions for the exploratory analysis and visualisation of such collected data.
With the increased availability of 3D eye tracking from new VR headsets, we are interesting in exploring the adaption of the software to support 3D analysis.
In this research project we aim to explore the current options for 3D visual eye tracking analysis, understand the adaptions the software needs, implement some of the important ones and test them with users.
We have various collaborators on the project all of which are happy to co-supervise you to help develop your understanding and network.
The current version of the software "webVETA" is currently under going evaluation of new features. You will be using and adding to this new version which is a web-based tool.
To get an idea of the software, we originally developed as a desktop application from 2019-2020 and written up here:
- Sarah Goodwin et al. VETA: Visual Eye-Tracking Analytics for the Exploration of Gaze Patterns and Behaviours, Visual Informatics, Volume 6, Issue 2, 2022, Pages 1-13, ISSN 2468-502X, https://doi.org/10.1016/j.visinf.2022.02.004
- video of VETA (desktop): https://www.youtube.com/watch?v=NsMP6eDtvgM