Classification images for aerial images capture visual expertise for binocular disparity and a prior for lighting from above

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Skog, EmilLuleå tekniska universitet,Hälsa, medicin och rehabilitering,School of Psychology, College of Health and Life Sciences, Aston University, Birmingham, B4 7ET, UK; Aston Laboratory for Immersive Virtual Environments, College of Health and Life Sciences, Aston University, Birmingham, B4 7ET, UK (författare)

Classification images for aerial images capture visual expertise for binocular disparity and a prior for lighting from above

Artikel/kapitelEngelska2024

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Association for Research in Vision and Ophthalmology,2024
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LIBRIS-ID:oai:DiVA.org:ltu-105079
https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-105079URI
https://doi.org/10.1167/jov.24.4.11DOI

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Validerad;2024;Nivå 2;2024-04-23 (signyg);Funder: Aston University; Ordnance Survey Ltd(9121572);Full text license: CC BY 4.0
Using a novel approach to classification images (CIs), we investigated the visual expertise of surveyors for luminance and binocular disparity cues simultaneously after screening for stereoacuity. Stereoscopic aerial images of hedges and ditches were classified in 10,000 trials by six trained remote sensing surveyors and six novices. Images were heavily masked with luminance and disparity noise simultaneously. Hedge and ditch images had reversed disparity on around half the trials meaning hedges became ditch-like and vice versa. The hedge and ditch images were also flipped vertically on around half the trials, changing the direction of the light source and completing a 2 × 2 × 2 stimulus design. CIs were generated by accumulating the noise textures associated with “hedge” and “ditch” classifications, respectively, and subtracting one from the other. Typical CIs had a central peak with one or two negative side-lobes. We found clear differences in the amplitudes and shapes of perceptual templates across groups and noise-type, with experts prioritizing binocular disparity and using this more effectively. Contrariwise, novices used luminance cues more than experts meaning that task motivation alone could not explain group differences. Asymmetries in the luminance CIs revealed individual differences for lighting interpretation, with experts less prone to assume lighting from above, consistent with their training on aerial images of UK scenes lit by a southerly sun. Our results show that (i) dual noise in images can be used to produce simultaneous CI pairs, (ii) expertise for disparity cues does not depend on stereoacuity, (iii) CIs reveal the visual strategies developed by experts, (iv) top-down perceptual biases can be overcome with long-term learning effects, and (v) CIs have practical potential for directing visual training.

Ämnesord och genrebeteckningar

NATURVETENSKAP Data- och informationsvetenskap Datorseende och robotik hsv//swe
NATURAL SCIENCES Computer and Information Sciences Computer Vision and Robotics hsv//eng
Psychology
Psykologi

Biuppslag (personer, institutioner, konferenser, titlar ...)

Meese, Timothy S.Aston Laboratory for Immersive Virtual Environments, College of Health and Life Sciences, Aston University, Birmingham, B4 7ET, UK (författare)
Sargent, Isabel M. J.Ordnance Survey, Adanac Drive, Southampton, SO16 0AS, UK; Electronics and Computer Science, University of Southampton, University Road, Southampton, SO17 1BJ, UK (författare)
Ormerod, AndrewOrdnance Survey, Adanac Drive, Southampton, SO16 0AS, UK (författare)
Schofield, Andrew J.School of Psychology, College of Health and Life Sciences, Aston University, Birmingham, B4 7ET, UK; Aston Laboratory for Immersive Virtual Environments, College of Health and Life Sciences, Aston University, Birmingham, B4 7ET, UK (författare)
Luleå tekniska universitetHälsa, medicin och rehabilitering (creator_code:org_t)

Sammanhörande titlar

Ingår i:Journal of Vision: Association for Research in Vision and Ophthalmology24:41534-7362

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Av författaren/redakt...: Skog, Emil; Meese, Timothy S ...; Sargent, Isabel ...; Ormerod, Andrew; Schofield, Andre ...

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