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J. Imaging 2018, 4(8), 96; https://doi.org/10.3390/jimaging4080096

Measuring the Spatial Noise of a Low-Cost Eye Tracker to Enhance Fixation Detection

1
Department of Geography, Ghent University, 9000 Gent, Belgium
2
Polytech Nantes, Laboratoire des Sciences du Numérique de Nantes (LS2N), Université de Nantes, 44306 Nantes CEDEX 3, France
3
Department of Surveying & Geoinformatics Engineering, University of West Attica, 12243 Aigaleo, Greece
*
Author to whom correspondence should be addressed.
Received: 1 June 2018 / Revised: 5 July 2018 / Accepted: 25 July 2018 / Published: 28 July 2018
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Abstract

The present study evaluates the quality of gaze data produced by a low-cost eye tracker (The Eye Tribe©, The Eye Tribe, Copenhagen, Denmark) in order to verify its suitability for the performance of scientific research. An integrated methodological framework, based on artificial eye measurements and human eye tracking data, is proposed towards the implementation of the experimental process. The obtained results are used to remove the modeled noise through manual filtering and when detecting samples (fixations). The outcomes aim to serve as a robust reference for the verification of the validity of low-cost solutions, as well as a guide for the selection of appropriate fixation parameters towards the analysis of experimental data based on the used low-cost device. The results show higher deviation values for the real test persons in comparison to the artificial eyes, but these are still acceptable to be used in a scientific setting. View Full-Text
Keywords: spatial noise; low-cost eye tracker; artificial eyes; fixation detection algorithm spatial noise; low-cost eye tracker; artificial eyes; fixation detection algorithm
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Ooms, K.; Krassanakis, V. Measuring the Spatial Noise of a Low-Cost Eye Tracker to Enhance Fixation Detection. J. Imaging 2018, 4, 96.

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