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Eye movements and information geometry
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0001-7557-4904
2016 (English)In: Optical Society of America. Journal A: Optics, Image Science, and Vision, ISSN 1084-7529, E-ISSN 1520-8532, Vol. 33, no 8, 1598-1603 p.Article in journal (Refereed) Published
Abstract [en]

The human visual system uses eye movements to gather visual information. They act as visual scanning processes and can roughly be divided into two different types: small movements around fixation points and larger movements between fixation points. The processes are often modeled as random walks, and recent models based on heavy tail distributions, also known as Lev\&\#x00FD; flights, have been used in these investigations. In contrast to these approaches we do not model the stochastic processes, but we will show that the step lengths of the movements between fixation points follow generalized Pareto distributions (GPDs). We will use general arguments from the theory of extreme value statistics to motivate the usage of the GPD and show empirically that the GPDs provide good fits for measured eye tracking data. In the framework of information geometry the GPDs with a common threshold form a two-dimensional Riemann manifold with the Fisher information matrix as a metric. We compute the Fisher information matrix for the GPDs and introduce a feature vector describing a GPD by its parameters and different geometrical properties of its Fisher information matrix. In our statistical analysis we use eye tracker measurements in a database with 15 observers viewing 1003 images under free-viewing conditions. We use Matlab functions with their standard parameter settings and show that a naive Bayes classifier using the eigenvalues of the Fisher information matrix provides a high classification rate identifying the 15 observers in the database.

Place, publisher, year, edition, pages
2016. Vol. 33, no 8, 1598-1603 p.
Keyword [en]
Vision - eye movements ; Vision modeling
National Category
Signal Processing
URN: urn:nbn:se:liu:diva-130590DOI: 10.1364/JOSAA.33.001598ISI: 000382005000020PubMedID: 27505658OAI: diva2:953349
Swedish Foundation for Strategic Research , IIS11-0081Swedish Research Council, 2014-6227

Funding agencies: Stiftelsen for Strategisk Forskning (SSF) [IIS11-0081]; Vetenskapsradet (VR) [2014-6227]

Available from: 2016-08-17 Created: 2016-08-17 Last updated: 2016-10-03

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Lenz, Reiner
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