Accéder directement au contenu Accéder directement à la navigation
Article dans une revue

Geometrically restricted image descriptors: A method to capture the appearance of shape.

Abstract : Shape perception varies depending on many factors. For example, presenting a stimulus in the periphery often yields a different appearance compared with its foveal presentation. However, how exactly shape appearance is altered under different conditions remains elusive. One reason for this is that studies typically measure identification performance, leaving details about target appearance unknown. The lack of appearance-based methods and general challenges to quantify appearance complicate the investigation of shape appearance. Here, we introduce Geometrically Restricted Image Descriptors (GRIDs), a method to investigate the appearance of shapes. Stimuli in the GRID paradigm are shapes consisting of distinct line elements placed on a grid by connecting grid nodes. Each line is treated as a discrete target. Observers are asked to capture target appearance by placing lines on a freely viewed response grid. We used GRIDs to investigate the appearance of letters and letter-like shapes. Targets were presented at 10° eccentricity in the right visual field. Gaze-contingent stimulus presentation was used to prevent eye movements to the target. The data were analyzed by quantifying the differences between targets and response in regard to overall accuracy, element discriminability, and several distinct error types. Our results show how shape appearance can be captured by GRIDs, and how a fine-grained analysis of stimulus parts provides quantifications of appearance typically not available in standard measures of performance. We propose that GRIDs are an effective tool to investigate the appearance of shapes.
Type de document :
Article dans une revue
Liste complète des métadonnées

https://hal.univ-lille.fr/hal-03259331
Contributeur : Lilloa Université de Lille Connectez-vous pour contacter le contributeur
Soumis le : lundi 14 juin 2021 - 09:36:21
Dernière modification le : jeudi 17 juin 2021 - 03:35:24
Archivage à long terme le : : jeudi 16 septembre 2021 - 08:21:13

Fichier

Melnik 2021 JoV.pdf
Fichiers éditeurs autorisés sur une archive ouverte

Licence


Distributed under a Creative Commons Paternité - Pas d'utilisation commerciale - Pas de modification 4.0 International License

Identifiants

Collections

Citation

Natalia Melnik, Daniel R Coates, Bilge Sayim. Geometrically restricted image descriptors: A method to capture the appearance of shape.. Journal of Vision, Association for Research in Vision and Ophthalmology, 2021, 21 (3), pp.14. ⟨10.1167/jov.21.3.14⟩. ⟨hal-03259331⟩

Partager

Métriques

Consultations de la notice

13

Téléchargements de fichiers

29