Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Object categorization via local kernels
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
2004 (English)In: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2 / [ed] Kittler, J; Petrou, M; Nixon, M, 2004, 132-135 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers the problem of multi-object categorization. We present an algorithm that combines support vector machines with local features via a new class of Mercer kernels. This class of kernels allows us to perform scalar products on feature vectors consisting of local descriptors, computed around interest points (like corners); these feature vectors are generally of different lengths for different images. The resulting framework is able to recognize multi-object categories in different settings, from lab-controlled to real-world scenes. We present several experiments, on different databases, and we benchmark our results with state-of-the-art algorithms for categorization, achieving excellent results.

Place, publisher, year, edition, pages
2004. 132-135 p.
Series
INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, ISSN 1051-4651
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-44312DOI: 10.1109/ICPR.2004.1334079ISI: 000223877400032Scopus ID: 2-s2.0-10044240377ISBN: 0-7695-2128-2 (print)OAI: oai:DiVA.org:kth-44312DiVA: diva2:451225
Conference
17th International Conference on Pattern Recognition (ICPR) Location: British Machine Vis Assoc, Cambridge, ENGLAND Date: AUG 23-26, 2004
Note
QC 20111025Available from: 2011-10-25 Created: 2011-10-20 Last updated: 2018-01-12Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Caputo, BarbaraNilsback, Maria-Elena
By organisation
Numerical Analysis and Computer Science, NADA
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 28 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf