Visual pathways for shape abstraction

Raftopoulos, KA; Kollias, SD

dc.contributor.author	Raftopoulos, KA	en
dc.contributor.author	Kollias, SD	en
dc.date.accessioned	2014-03-01T02:53:31Z
dc.date.available	2014-03-01T02:53:31Z
dc.date.issued	2011	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36384
dc.subject	Shape Abstraction	en
dc.subject	Skeleton Transform	en
dc.subject	Visual Pathways	en
dc.subject.other	2D shape recognition	en
dc.subject.other	Boundary curvature	en
dc.subject.other	Boundary information	en
dc.subject.other	Cortical neurons	en
dc.subject.other	Local curvature	en
dc.subject.other	Medial axis transforms	en
dc.subject.other	Multilayered neural networks	en
dc.subject.other	Proposed architectures	en
dc.subject.other	Receptive fields	en
dc.subject.other	Shape Abstraction	en
dc.subject.other	Shape representation	en
dc.subject.other	Skeleton transform	en
dc.subject.other	State of the art	en
dc.subject.other	Visual cortexes	en
dc.subject.other	Visual pathways	en
dc.subject.other	Abstracting	en
dc.subject.other	Musculoskeletal system	en
dc.subject.other	Network layers	en
dc.subject.other	Vision	en
dc.subject.other	Neural networks	en
dc.title	Visual pathways for shape abstraction	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-21735-7_36	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-21735-7_36	en
heal.publicationDate	2011	en
heal.abstract	The Medial Axis Transform (MAT) (or skeleton transform) is one of the most studied shape representation techniques with established advantages for general 2D shape recognition. Embedding local boundary information in the skeleton, in particular, has been shown to improve 2D shape recognition capability to state of the art levels. In this paper we present a visual pathway for extracting an analogous to the MAT skeleton abstraction of shape that also contains local boundary curvature information. We refer to this structure with the term curvature-skeleton. The proposed architecture is inspired by the biological findings regarding the cortical neurons of the visual cortex and their special purpose Receptive Fields (RFs). Points of high curvature are initially identified and subsequently combined by means of a visual pathway that achieves an analogous to the MAT abstraction of shape but also embeds in the skeleton local curvature information of the shape's boundary. We present experimental results illustrating that such an abstraction can improve the recognition capability of multi layered neural network classifiers. © 2011 Springer-Verlag.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-21735-7_36	en
dc.identifier.volume	6791 LNCS	en
dc.identifier.issue	PART 1	en
dc.identifier.spage	291	en
dc.identifier.epage	298	en