A texture-processing model of the ‘visual sense of number’
Author(s) -
Michael J. Morgan,
S. Raphael,
Marc S. Tibber,
Steven C. Dakin
Publication year - 2014
Publication title -
proceedings of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.342
H-Index - 253
eISSN - 1471-2954
pISSN - 0962-8452
DOI - 10.1098/rspb.2014.1137
Subject(s) - numerosity adaptation effect , contrast (vision) , artificial intelligence , texture (cosmology) , perception , computer science , pattern recognition (psychology) , computer vision , energy (signal processing) , mathematics , image (mathematics) , psychology , statistics , neuroscience
It has been suggested that numerosity is an elementary quality of perception, similar to colour. If so (and despite considerable investigation), its mechanism remains unknown. Here, we show that observers require on average a massive difference of approximately 40% to detect a change in the number of objects that vary irrelevantly in blur, contrast and spatial separation, and that some naive observers require even more than this. We suggest that relative numerosity is a type of texture discrimination and that a simple model computing the contrast energy at fine spatial scales in the image can perform at least as well as human observers. Like some human observers, this mechanism finds it harder to discriminate relative numerosity in two patterns with different degrees of blur, but it still outpaces the human. We propose energy discrimination as a benchmark model against which more complex models and new data can be tested.
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