End-Stop Exemplar Based Recognition

Søren I. Olsen

doi:10.1007/3-540-45103-X_7

End-Stop Exemplar Based Recognition

Søren I. Olsen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

1 Citation (Scopus)

Abstract

An approach to exemplar based recognition of visual shapes is presented. The shape information is described by attributed interest points (keys) detected by an end-stop operator. The attributes describe the statistics of lines and edges local to the interest point, the position of neighboring interest points, and (in the training phase) a list of recognition names. Recognition is made by a simple voting procedure. Preliminary experiments indicate that the recognition is robust to noise, small deformations, background clutter and partial occlusion.

Original language	English
Title of host publication	Image Analysis : 13th Scandinavian Conference, SCIA 2003 Halmstad, Sweden, June 29 – July 2, 2003 Proceedings
Publication date	2003
Pages	257-266
DOIs	https://doi.org/10.1007/3-540-45103-X_7
Publication status	Published - 2003
Event	13th Scandinavian Conference in Image Analysis - SCIA - Halmstad, Sweden Duration: 29 Nov 2010 → … Conference number: 13

Conference

Conference	13th Scandinavian Conference in Image Analysis - SCIA
Number	13
Country/Territory	Sweden
City	Halmstad
Period	29/11/2010 → …

Series	Lecture notes in computer science
Volume	2749/2003
ISSN	0302-9743

Access to Document

10.1007/3-540-45103-X_7

http://www.springerlink.de/content/1c361a9edvhbt63t/fulltext.pdf

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Check availability at the Royal Danish Library

Cite this

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title = "End-Stop Exemplar Based Recognition",

abstract = "An approach to exemplar based recognition of visual shapes is presented. The shape information is described by attributed interest points (keys) detected by an end-stop operator. The attributes describe the statistics of lines and edges local to the interest point, the position of neighboring interest points, and (in the training phase) a list of recognition names. Recognition is made by a simple voting procedure. Preliminary experiments indicate that the recognition is robust to noise, small deformations, background clutter and partial occlusion.",

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