Getting more out of Area of Interest (AOI) analysis with SPLOT
Autor: | Belopolsky, Artem V., Spencer, Stephen N. |
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Přispěvatelé: | Cognitive Psychology, IBBA, Spencer, Stephen N. |
Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
business.industry
Computer science Eye movement dynamics Eye Tracking Eye movement Pattern recognition Area of interest Area Of Interest analysis Cluster-based permutation Visualization Workflow Permutation testing Eye tracking Proportion of looks over time Statistical analysis Artificial intelligence business |
Zdroj: | ETRA 2020 Short Papers: ACM Symposium on Eye Tracking Research and Applications, 1-4 STARTPAGE=1;ENDPAGE=4;TITLE=ETRA 2020 Short Papers ETRA Short Papers Belopolsky, A V 2020, Getting more out of Area of Interest (AOI) analysis with SPLOT . in S N Spencer (ed.), ETRA 2020 Short Papers : ACM Symposium on Eye Tracking Research and Applications ., 18, Eye Tracking Research and Applications Symposium (ETRA), Association for Computing Machinery, pp. 1-4, 2020 ACM Symposium on Eye Tracking Research and Applications, ETRA 2020, Stuttgart, Germany, 2/06/20 . https://doi.org/10.1145/3379156.3391372 |
DOI: | 10.1145/3379156.3391372 |
Popis: | To analyze eye-tracking data the viewed image is often divided into areas of interest (AOI). However, the temporal dynamics of eye movements towards the AOI is often lost either in favor of summary statistics (e.g., proportion of fixations or dwell time) or is significantly reduced by "binning" the data and computing the same summary statistic over each time bin. This paper introduces SPLOT: smoothed proportion of looks over time method for analyzing the eye movement dynamics across AOI. SPLOT comprises of a complete workflow, from visualization of the time-course to performing statistical analysis on it using cluster-based permutation testing. The possibilities of SPLOT are illustrated by applying it to an existing dataset of eye movements of radiologists diagnosing a chest X-ray. |
Databáze: | OpenAIRE |
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