Entropy-based Statistical Analysis of Eye Movement Transitions
Krzysztof Krejtz , Tomasz Szmidt , Andrew T. Duchowski , Izabela Krejtz
AbstractThe paper introduces a two-step method of quantifying eye movement transitions between Areas of Interests (AOIs). First, individuals' gaze switching patterns, represented by fixated AOI sequences, are modeled as Markov chains. Second, Shannon's entropy coefficient of the fit Markov model is computed to quantify the complexity of individual switching patterns. To determine the overall distribution of attention over AOIs, the entropy coefficient of individuals' stationary distribution of fixations is calculated. The novelty of the method is that it captures the variability of individual differences in eye movement characteristics, which are then summarized statistically. The method is demonstrated on gaze data collected during free viewing of classical art paintings. Shannon's coefficient derived from individual transition matrices is significantly related to participants' individual differences as well as to their aesthetic experience of art pieces.
|Publication size in sheets||0.5|
|Book||Qvarfordt Pernilla , Witzner Hansen Dan (eds.): ETRA '14 Proceedings of the Symposium on Eye Tracking Research and Applications, 2014, ACM, ISBN 978-1-4503-2751, DOI:10.1145/2578153.2578176|
|Keywords in English||eye movements, transition matrix, Shannon entropy, Markov model, gaze distribution|
|Citation count*||40 (2020-09-25)|
|Dorobek Naukowy - Preview URL||http://dn.swps.edu.pl/Podglad.aspx?WpisID=15258|
|Dorobek Naukowy - Approve URL||http://dn.swps.edu.pl/Biuro/ZatwierdzanieWpisu.aspx?WpisID=15258|
|Dorobek Naukowy - Preview URL||http://dn.swps.edu.pl/Podglad.aspx?WpisID=16703|
|Dorobek Naukowy - Approve URL||http://dn.swps.edu.pl/Biuro/ZatwierdzanieWpisu.aspx?WpisID=16703|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.