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
Cue integration through discriminative accumulation
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
2004 (English)In: PROCEEDINGS OF THE 2004 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 2, 2004, 578-585 p.Conference paper, Published paper (Refereed)
Abstract [en]

Object recognition systems aiming to work in real world settings should use multiple cues in order to achieve robustness. We present a new cue integration scheme which extends the idea of cue accumulation to discriminative classifiers. We derive and test the scheme for Support Vector Machines (SVMs), but we also show that it is easily extendible to any large margin classifier Interestingly, in the case of one-class SVMs, the scheme can be interpreted as a new class of Mercer kernels for multiple cues. Experimental comparison with a probabilistic accumulation scheme is favorable to our method. Comparison with voting scheme shows that our method may suffer as the number of object classes increases. Based on these results, we propose a recognition algorithm consisting of a decision tree where decisions at each node are taken using our accumulation scheme. Results obtained using this new algorithm compare very favorably to accumulation (both probabilistic and discriminative) and voting scheme.

Place, publisher, year, edition, pages
2004. 578-585 p.
Series
PROCEEDINGS - IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, ISSN 1063-6919 ; 2
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-44319ISI: 000223605500076Scopus ID: 2-s2.0-5044236501ISBN: 0-7695-2158-4 (print)OAI: oai:DiVA.org:kth-44319DiVA: diva2:451196
Conference
Conference on Computer Vision and Pattern Recognition Location: Washington, DC Date: JUN 27-JUL 02, 2004
Note
QC 20111025Available from: 2011-10-25 Created: 2011-10-20 Last updated: 2011-11-02Bibliographically approved

Open Access in DiVA

No full text

Scopus

Search in DiVA

By author/editor
Nilsback, Maria ElenaCaputo, Barbara
By organisation
Numerical Analysis and Computer Science, NADA
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 20 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