Affective computing with eye-tracking data in the study of the visual perception of architectural spaces
| Autor: | Mariusz Dzieńkowski, Magdalena Chmielewska, Jacek Bogucki, Wojciech Kocki, Wioletta Tuszyńska-Bogucka, Jarosław Pełka, Bartłomiej Kwiatkowski |
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| Rok vydání: | 2019 |
| Předmět: |
Visual perception
genetic structures Artificial neural network business.industry 05 social sciences Eye movement Pattern recognition eye diseases 050105 experimental psychology 03 medical and health sciences 0302 clinical medicine Binary classification lcsh:TA1-2040 Pupillary response Selection (linguistics) Eye tracking 0501 psychology and cognitive sciences sense organs Artificial intelligence lcsh:Engineering (General). Civil engineering (General) Affective computing business 030217 neurology & neurosurgery |
| Zdroj: | MATEC Web of Conferences, Vol 252, p 03021 (2019) |
| 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. |
| Databáze: | OpenAIRE |
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