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Combining eye-tracking data with an analysis of video content from free-viewing a video of a walk in an urban park environment
Amati, Marco McCarthy, Chris Parmehr, Ebadat Ghanbari Sita, Jodi
Amati, Marco
McCarthy, Chris
Parmehr, Ebadat Ghanbari
Sita, Jodi
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Abstract
As individuals increasingly live in cities, methods to study their everyday movements and the data that can be collected becomes important and valuable. Eye-tracking informatics are known to connect to a range of feelings, health conditions, mental states and actions. But because vision is the result of constant eye-movements, teasing out what is important from what is noise is complex and data intensive. Furthermore, a significant challenge is controlling for what people look at compared to what is presented to them.
The following presents a methodology for combining and analyzing eye-tracking on a video of a natural and complex scene with a machine learning technique for analyzing the content of the video. In the protocol we focus on analyzing data from filmed videos, how a video can be best used to record participants' eye-tracking data, and importantly how the content of the video can be analyzed and combined with the eye-tracking data. We present a brief summary of the results and a discussion of the potential of the method for further studies in complex environments.
Keywords
Date
2019
Type
Journal article
Journal
Journal of Visualized Experiments
Book
Volume
Issue
147
Page Range
1-9
Article Number
Article e58459
ACU Department
Faculty of Health Sciences
Relation URI
DOI
Source URL
Event URL
Open Access Status
License
All rights reserved
File Access
Controlled