End-Stop Exemplar Based Recognition

Søren I. Olsen

doi:10.1007/3-540-45103-X_7

End-Stop Exemplar Based Recognition

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

Cite this

@inproceedings{86133b706dd211dd8d9f000ea68e967b,

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.",

author = "Olsen, {S{\o}ren I.}",

year = "2003",

doi = "10.1007/3-540-45103-X_7",

language = "English",

series = "Lecture notes in computer science",

publisher = "Springer",

pages = "257--266",

booktitle = "Image Analysis",

note = "13th Scandinavian Conference in Image Analysis - SCIA ; Conference date: 29-11-2010",

}

TY - GEN

T1 - End-Stop Exemplar Based Recognition

AU - Olsen, Søren I.

N1 - Conference code: 13

PY - 2003

Y1 - 2003

N2 - 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.

AB - 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.

U2 - 10.1007/3-540-45103-X_7

DO - 10.1007/3-540-45103-X_7

M3 - Article in proceedings

T3 - Lecture notes in computer science

SP - 257

EP - 266

BT - Image Analysis

T2 - 13th Scandinavian Conference in Image Analysis - SCIA

Y2 - 29 November 2010

ER -

End-Stop Exemplar Based Recognition

Abstract

Conference

Access to Document

Fingerprint

Cite this