The Salient360! toolbox: Handling gaze data in 3D made easy
Eye tracking has historically been a very popular tool. The data it records allow us to understand how people behave and what they attend to within our visual world; under this perspective the experiments, applications and use-cases are endless. Therefore, it is not surprising to witness a strong ri...
Saved in:
Published in: | Computers & graphics Vol. 119; p. 103890 |
---|---|
Main Authors: | , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Elsevier Ltd
01-04-2024
Elsevier |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Eye tracking has historically been a very popular tool. The data it records allow us to understand how people behave and what they attend to within our visual world; under this perspective the experiments, applications and use-cases are endless. Therefore, it is not surprising to witness a strong rise in the use of eXtended Reality (XR) devices with embedded eye trackers in research. These devices allow for less obtrusive experimenting conditions, and a significantly higher experimental control compared to traditional desktop testing. The use of eye tracking in XR is increasing and so is the need for a toolbox enabling consensus about eye tracking methods in 3D. We present the Salient360! toolbox: it implements functions to identify saccades and fixations and output gaze features (e.g., saccade directions) to generate saliency maps, fixation maps, and scanpath data. It implements comparisons of gaze data with methods adapted to 3D. We plan continuous improvements of the toolbox as the community develops new tools and methods dedicated to 360°gaze tracking. We hope that this toolbox will spark discussions about the methodology of 3D gaze processing, facilitate running experiments, and improve studying gaze in 3D.
https://github.com/David-Ef/salient360Toolbox
[Display omitted]
•We share with the community a toolbox for handling gaze data in 3D (e.g., XR).•The toolbox is made to process, compare, and visualise gaze data.•We present and explain implementation choices for several important aspects of the toolbox. |
---|---|
ISSN: | 0097-8493 1873-7684 |
DOI: | 10.1016/j.cag.2024.103890 |