Analyzing Eye Paths Using Fractals.
Eye paths
Eye tracking
Fractal
Perception
Scanpaths
Journal
Advances in neurobiology
ISSN: 2190-5215
Titre abrégé: Adv Neurobiol
Pays: United States
ID NLM: 101571545
Informations de publication
Date de publication:
2024
2024
Historique:
medline:
12
3
2024
pubmed:
12
3
2024
entrez:
12
3
2024
Statut:
ppublish
Résumé
Visual patterns reflect the anatomical and cognitive background underlying process governing how we perceive information, influenced by stimulus characteristics and our own visual perception. These patterns are both spatially complex and display self-similarity seen in fractal geometry at different scales, making them challenging to measure using the traditional topological dimensions used in Euclidean geometry.However, methods for measuring eye gaze patterns using fractals have shown success in quantifying geometric complexity, matchability, and implementation into machine learning methods. This success is due to the inherent capabilities that fractals possess when reducing dimensionality using Hilbert curves, measuring temporal complexity using the Higuchi fractal dimension (HFD), and determining geometric complexity using the Minkowski-Bouligand dimension.Understanding the many applications of fractals when measuring and analyzing eye gaze patterns can extend the current growing body of knowledge by identifying markers tied to neurological pathology. Additionally, in future work, fractals can facilitate defining imaging modalities in eye tracking diagnostics by exploiting their capability to acquire multiscale information, including complementary functions, structures, and dynamics.
Identifiants
pubmed: 38468066
doi: 10.1007/978-3-031-47606-8_42
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
827-848Informations de copyright
© 2024. The Author(s), under exclusive license to Springer Nature Switzerland AG.
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