Scene categorization at large visual eccentricities - Université de Lille Accéder directement au contenu
Article Dans Une Revue Vision Research Année : 2013

Scene categorization at large visual eccentricities

Résumé

Studies of scene perception have shown that the visual system is particularly sensitive to global properties such as the overall layout of a scene. Such global properties cannot be computed locally, but rather require relational analysis over multiple regions. To what extent is observers' perception of scenes impaired in the far periphery? We examined the perception of global scene properties (Experiment 1) and basic-level categories (Experiment 2) presented in the periphery from 10° to 70°. Pairs of scene photographs were simultaneously presented left and right of fixation for 80ms on a panoramic screen (5m diameter) covering the whole visual field while central fixation was controlled. Observers were instructed to press a key corresponding to the spatial location left/right of a pre-defined target property or category. The results show that classification of global scene properties (e.g., naturalness, openness) as well as basic-level categorization (e.g., forests, highways), while better near the center, were accomplished with a performance highly above chance (around 70% correct) in the far periphery even at 70° eccentricity. The perception of some global properties (e.g., naturalness) was more robust in peripheral vision than others (e.g., indoor/outdoor) that required a more local analysis. The results are consistent with studies suggesting that scene gist recognition can be accomplished by the low resolution of peripheral vision.

Dates et versions

hal-03031463 , version 1 (30-11-2020)

Identifiants

Citer

Muriel Boucart, Christine Moroni, Miguel Thibaut, Sebastien Szaffarczyk, Michelle Greene. Scene categorization at large visual eccentricities. Vision Research, 2013, Vision research, 86, pp.35-42. ⟨10.1016/j.visres.2013.04.006⟩. ⟨hal-03031463⟩
19 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More