2017/03/27 by Ioannis Rigas, Lee Friedman, Rigas, Ioannis +4
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Biological sciences #FOS: Computer and information sciences #Gaze Tracking and Assistive Technology #Human-Computer Interaction (cs.HC) #Quantitative Methods (q-bio.QM)
paper · pdf · doi:10.48550/arxiv.1703.09167
openalex publication_date 2017/03/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This work presents a study on the extraction and analysis of a set of 101\ncategories of eye movement features from three types of eye movement events:\nfixations, saccades, and post-saccadic oscillations. The eye movements were\nrecorded during a reading task. For the categories of features with multiple\ninstances in a recording we extract corresponding feature subtypes by\ncalculating descriptive statistics on the distributions of these instances. A\nunified framework of detailed descriptions and mathematical formulas are\nprovided for the extraction of the feature set. The analysis of feature values\nis performed using a large database of eye movement recordings from a normative\npopulation of 298 subjects. We demonstrate the central tendency and overall\nvariability of feature values over the experimental population, and more\nimportantly, we quantify the test-retest reliability (repeatability) of each\nseparate feature. The described methods and analysis can provide valuable tools\nin fields exploring the eye movements, such as in behavioral studies, attention\nand cognition research, medical research, biometric recognition, and\nhuman-computer interaction.\n