Good continuation in dot patterns : A quantitative approach based on local symmetry and non-accidentalness

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

8 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)183-191
Journal / PublicationVision Research
Volume126
Publication statusPublished - 1 Sept 2016
Externally publishedYes

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.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review