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Eyetracker data analysis

Supervisors

Suitable for

MSc in Computer Science

Abstract

Eyetracking allows researchers to identify where observers look on a monitor. A challenge in analysing eyetracker output however is identifying patterns of viewing behaviour from the raw eyetracker logs over time and what they mean in a research context, particularly as no semantic information about the pixel being viewed is considered. In practice, this means that we know where someone is looking, but nothing about what it means to look at that pixel or the order of pixels. From a research perspective, being able to tag areas of interest, and what those areas mean, or conduct other statistical analysis on viewing patterns would be of significant use to analysing results, particularly if these results could be automated. The purpose of this project is to conduct an eyetracker experiment, and design and implement useful methods to analyse eyetracker data. We will be able to provide training for the student, so they are able to use the eyetracking tools themselves. Other eyetracking projects also possible, depending on interest and inspiration.

Skills: Programming, Statistics