Discriminative Shape Alignment

M. Loog; M. de Bruijne

doi:10.1007/978-3-642-02498-6_38

Discriminative Shape Alignment

M. Loog, M. de Bruijne

Department of Computer Science

4 Citations (Scopus)

Abstract

The alignment of shape data to a common mean before its subsequent processing is an ubiquitous step within the area shape analysis. Current approaches to shape analysis or, as more specifically considered in this work, shape classification perform the alignment in a fully unsupervised way, not taking into account that eventually the shapes are to be assigned to two or more different classes. This work introduces a discriminative variation to well-known Procrustes alignment and demonstrates its benefit over this classical method in shape classification tasks. The focus is on two-dimensional shapes from a two-class recognition problem.

Original language	English
Title of host publication	Information Processing in Medical Imaging
Number of pages	7
Volume	5636/2009
Publisher	Springer
Publication date	2009
Pages	459-466
ISBN (Print)	978-642-02497-9
DOIs	https://doi.org/10.1007/978-3-642-02498-6_38
Publication status	Published - 2009
Event	Information Processing in Medical Imaging 2009 (IPMI ´09) - Williamsburg, VA, United States Duration: 5 Jul 0009 → 10 Jul 0009 Conference number: 21

Conference

Conference	Information Processing in Medical Imaging 2009 (IPMI ´09)
Number	21
Country/Territory	United States
City	Williamsburg, VA
Period	05/07/0009 → 10/07/0009

Series	Lecture notes in computer science
Volume	5636
ISSN	0302-9743

Access to Document

10.1007/978-3-642-02498-6_38

Cite this

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