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Lirias
Article . 1993
Data sources: Lirias
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Biological Cybernetics
Article . 1993 . Peer-reviewed
License: Springer TDM
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zbMATH Open
Article . 1993
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DBLP
Article . 2020
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Viewpoint-invariant Weber fractions and standard contour-curvature discrimination

Authors: David H. Foster; Johan Wagemans;

Viewpoint-invariant Weber fractions and standard contour-curvature discrimination

Abstract

It is proposed that any cue for the visual discrimination of shape, in particular the discrimination of curved contours, should be such that the perceptual relationships defined by the cue are invariant under changes in observer viewpoint. Such relationships may be quantified by the Weber fraction; that is, the ratio Δc/c, where, for any particular value c of the cue, Δc is the smallest difference in c that can be detected. Eight geometric attributes of curved contours having one symmetry axis and parallel chords (a standard stimulus configuration) were examined for invariance of the Weber fraction under symmetry-preserving affine transformations of the image plane (changes in viewpoint are well approximated by affine transformations when depth is small relative to viewing distance). The attributes, each investigated in previous psychophysical studies, were equivalent-curvature, radius-of-curvature, turning-angle, arc-length-divided-by-chord-length, arc-length, maximum-deviation (sag), area, and mean-deviation. Three of the attributes, namely sag, area, and mean-deviation, satisfied the viewpoint-invariance condition; the remainder failed. These results are considered in relation to previously published empirical data on the Weber fraction for contour-curvature discrimination. © 1993 Springer-Verlag.

Countries
Belgium, United Kingdom
Related Organizations
Keywords

Technology, Science & Technology, Neurology & Neurosurgery, MOTION, Psychophysics and psychophysiology; perception, 0299 Other Physical Sciences, 1702 Cognitive Sciences, Neurosciences, 4601 Applied computing, shape, curved lines, motion, CURVED LINES, Computer Science, 3209 Neurosciences, 0801 Artificial Intelligence and Image Processing, 3102 Bioinformatics and computational biology, Computer Science, Cybernetics, SHAPE, Neurosciences & Neurology, Life Sciences & Biomedicine

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Average
Green
bronze