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Predicting Fixations with Computational Algorithms

Nederveen, A. (2007) Predicting Fixations with Computational Algorithms. Master's Thesis / Essay, Artificial Intelligence.

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Abstract

Our eyes make several movements per second. When, for example, reading this line of text, our eyes constantly move to different parts of the sentence. These eye movements or saccacles are interleaved by fixations. Fixations are periods of about 200 ms in which the eye has a relative fixed position, which serves to center our fovea, the most acute part of our retina, on the object of interest. Because the fovea covers only 2 degrees of our visual field, we only select a small part of a scene at once. We are interested which part of scene is selected and to what extend we can predict those parts by using computational algorithms.We conducted an eye tracker experiment to obtain data from human participants and compared the data to several algorithms. Particular attention was given to the algorithms based on symmetry. We found that the performance of the algorithms based on symmetry compares favorable to other tested algorithms such as, among others, the saliency model by Itti, Koch, and Niebur (1998), a well known computational bottom-up model of visual attention.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Artificial Intelligence
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 07:30
Last Modified: 15 Feb 2018 07:30
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/9072

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