Affective computing with eye-tracking data in the study of the visual perception of architectural spaces

Autor: Chmielewska Magdalena, Dzieńkowski Mariusz, Bogucki Jacek, Kocki Wojciech, Kwiatkowski Bartłomiej, Pełka Jarosław, Tuszyńska-Bogucka Wioletta
Jazyk: English<br />French
Rok vydání: 2019
Předmět:
Zdroj: MATEC Web of Conferences, Vol 252, p 03021 (2019)
Druh dokumentu: article
ISSN: 2261-236X
DOI: 10.1051/matecconf/201925203021
Popis: In the presented study the usefulness of eye-tracking data for classification of architectural spaces as stressful or relaxing was examined. The eye movements and pupillary response data were collected using the eye-tracker from 202 adult volunteers in the laboratory experiment in a well-controlled environment. Twenty features were extracted from the eye-tracking data and after the selection process the features were used in automated binary classification with a variety of machine learning classifiers including neural networks. The results of the classification using eye-tracking data features yielded 68% accuracy score, which can be considered satisfactory. Moreover, statistical analysis showed statistically significant differences in eye activity patterns between visualisations labelled as stressful or relaxing.
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