Good continuation in dot patterns : A quantitative approach based on local symmetry and non-accidentalness
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 183-191 |
Journal / Publication | Vision Research |
Volume | 126 |
Publication status | Published - 1 Sept 2016 |
Externally published | Yes |
Link(s)
Abstract
We propose a novel approach to the grouping of dot patterns by the good continuation law. Our model is based on local symmetries, and the non-accidentalness principle to determine perceptually relevant configurations. A quantitative measure of non-accidentalness is proposed, showing a good correlation with the visibility of a curve of dots. A robust, unsupervised and scale-invariant algorithm for the detection of good continuation of dots is derived. The results of the proposed method are illustrated on various datasets, including data from classic psychophysical studies. An online demonstration of the algorithm allows the reader to directly evaluate the method. © 2015 Elsevier Ltd
Research Area(s)
- Dots, Gestalt, Good continuation, Local symmetry, Non-accidentalness
Bibliographic Note
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Citation Format(s)
Good continuation in dot patterns: A quantitative approach based on local symmetry and non-accidentalness. / Lezama, José; Randall, Gregory; Morel, Jean-Michel et al.
In: Vision Research, Vol. 126, 01.09.2016, p. 183-191.
In: Vision Research, Vol. 126, 01.09.2016, p. 183-191.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review