| 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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