Performance and confusion effects for gist perception of scenes: an investigation of expertise, viewpoint, and image categories

Abstract

Human object recognition often exhibits viewpoint invariance. However, unfamiliar aerial viewpoints pose challenges because diagnostic features are often obscured. Here, we investigated the gist perception of scenes when viewed from above and at the ground level, comparing novices against remote sensing surveyors with expertise in aerial photogrammetry. In a randomly interleaved single-interval, 14-choice design, briefly presented target images were followed by a backward white-noise mask. The targets and choices were selected from seven natural and seven man-made categories. Performance across expertise and viewpoint was between 46.0% and 82.6% correct and confusions were sparsely distributed across the 728 (2 × 2 × 14 × 13) possibilities. Both groups performed better with ground views than with aerial views and different confusions were made across viewpoints, but experts outperformed novices only for aerial views, displaying no transfer of expertise to ground views. Where novices underperformed by comparison, this tended to involve mistaking natural for man-made scenes in aerial views. There was also an overall effect for categorisation to be better for the man-made categories than the natural categories. These, and a few other notable exceptions aside, the main result was that detailed sub-category patterns of successes and confusions were very similar across participant groups: the experimental effects related more to viewpoint than expertise. This contrasts with our recent finding for perception of 3D relief, where comparable groups of experts and novices used very different strategies. It seems that expertise in gist perception (for aerial images at least) is largely a matter of degree rather than kind.

Publication DOI: https://doi.org/10.1177/03010066251345677
Divisions: College of Health & Life Sciences > School of Optometry > Optometry
College of Health & Life Sciences > School of Optometry > Optometry & Vision Science Research Group (OVSRG)
College of Health & Life Sciences > Clinical and Systems Neuroscience
College of Health & Life Sciences > School of Psychology
College of Health & Life Sciences
Aston University (General)
Funding Information: ES was supported by funding from Aston University (UK), Ordnance Survey Ltd (company number 9121572) and a grant from Kempestiftelserna (JCSMK23-0179).
Additional Information: Copyright © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Publication ISSN: 1468-4233
Data Access Statement: Editable files of the raw data for each observer are available from DOI: https://doi.org/10.17036/researchdata.aston.ac.uk.00000640
Last Modified: 27 Jun 2025 07:13
Date Deposited: 24 Jun 2025 10:44
Full Text Link:
Related URLs: https://journal ... 010066251345677 (Publisher URL)
PURE Output Type: Article
Published Date: 2025-06-24
Published Online Date: 2025-06-24
Accepted Date: 2025-05-12
Authors: Skog, Emily
Schofield, Andrew J. (ORCID Profile 0000-0002-0589-4678)
Meese, Timothy S. (ORCID Profile 0000-0003-3744-4679)

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