An unsupervised algorithm for detecting good continuation in Dot Patterns
Resumen:
In this article we describe an algorithm for the automatic detection of perceptually relevant configurations of `good continuation' of points in 2D point patterns. The algorithm is based on the `a contrario' detection theory and on the assumption that `good continuation' of points are locally quasi-symmetric. The algorithm has only one critical parameter, which controls the number of false detections.
2017 | |
Good continuation Gestalt Dots Non-accidentalness Local symmetry |
|
Inglés | |
Universidad de la República | |
COLIBRI | |
http://hdl.handle.net/20.500.12008/8904 | |
Acceso abierto | |
Licencia Creative Commons Atribución – No Comercial – Sin Derivadas (CC BY-NC-SA 4.0) |
Resultados similares
-
Good continuation in dot patterns : A quantitative approach based on local symmetry and non-accidentalness
Autor(es):: Lezama, José
Fecha de publicación:: (2015) -
A contrario detection of good continuation of points
Autor(es):: Morel, Jean-Michel
Fecha de publicación:: (2014) -
An unsupervised point alignment detection algorithm
Autor(es):: Lezama, Jorge
Fecha de publicación:: (2015) -
An unsupervised point alignment detection algorithm
Autor(es):: Lezama, José
Fecha de publicación:: (2015) -
Robust and unsupervised perceptual grouping of curves of dots
Autor(es):: Lezama, José
Fecha de publicación:: (2016)