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Shape as an emergent property

Jermyn, Ian H.

Authors



Contributors

S.J. Dickinson
Editor

Z. Pizlo
Editor

Abstract

Shape is a ubiquitous property of our world. Inferences about it require ‘shape models’: probability distributions on shapes. The crucial property of any such shape model is the existence of long-range dependencies between boundary points. We look at how this property has typically been implemented in machine vision, and at the drawbacks of this ‘classical’ approach. We then discuss an alternative, inspired by classes of shapes arising in certain image processing problems. The resulting description of shape does not involve exogenous templates, but instead describes shape as an emergent property of interactions in a network of simple nodes.

Citation

Jermyn, I. H. (2013). Shape as an emergent property. In S. Dickinson, & Z. Pizlo (Eds.), Shape perception in human and computer vision : an interdisciplinary perspective (187-199). Springer Verlag. https://doi.org/10.1007/978-1-4471-5195-1_13

Publication Date Jan 1, 2013
Deposit Date Jul 27, 2015
Publisher Springer Verlag
Pages 187-199
Series Title Advances in computer vision and pattern recognition
Book Title Shape perception in human and computer vision : an interdisciplinary perspective.
ISBN 9781447151944
DOI https://doi.org/10.1007/978-1-4471-5195-1_13


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