2D Geometry Predicts Perceived Visual Curvature in Context-Free Viewing
Author
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-05
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Planar geometry was exploited for the computation of symmetric visual curves in the image plane, with consistent variations in local parameters such as sagitta, chordlength, and the curves’ height-to-width ratio, an indicator of the visual area covered by the curve, also called aspect ratio.
Image representations of single curves (no local image context) were presented to human observers to measure their visual sensation of curvature magnitude elicited by a given curve.
Nonlinear regression analysis was performed on both the individual and the average data using two types of model: (1) a power function where y (sensation) tends towards infinity as a function of x (stimulus input), most frequently used to model sensory scaling data for sensory continua, and (2) an “exponential rise to maximum” function, which converges towards an asymptotically stable level of y as a function of x .
Both models provide satisfactory fits to subjective curvature magnitude as a function of the height-to-width ratio of single curves.
The findings are consistent with an in-built sensitivity of the human visual system to local curve geometry, a potentially essential ground condition for the perception of concave and convex objects in the real world.
American Psychological Association (APA)
Dresp-Langley, Birgitta. 2015. 2D Geometry Predicts Perceived Visual Curvature in Context-Free Viewing. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1057738
Modern Language Association (MLA)
Dresp-Langley, Birgitta. 2D Geometry Predicts Perceived Visual Curvature in Context-Free Viewing. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1057738
American Medical Association (AMA)
Dresp-Langley, Birgitta. 2D Geometry Predicts Perceived Visual Curvature in Context-Free Viewing. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1057738
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057738