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Recognizing human actions: A local SVM approach
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.ORCID iD: 0000-0003-3439-0468
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.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 3 / [ed] Kittler, J; Petrou, M; Nixon, M, 2004, 32-36 p.Conference paper, Published paper (Refereed)
Abstract [en]

Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper we demonstrate how such features can be used for recognizing complex motion patterns. We construct video representations in terms of local space-time features and integrate such representations with SVM classification schemes for recognition. For the purpose of evaluation we introduce a new video database containing 2391 sequences of six human actions performed by 25 people in four different scenarios. The presented results of action recognition justify the proposed method and demonstrate its advantage compared to other relative approaches for action recognition.

Place, publisher, year, edition, pages
2004. 32-36 p.
Series
INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, ISSN 1051-4651
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-44315DOI: 10.1109/ICPR.2004.1334462ISI: 000223879500009Scopus ID: 2-s2.0-10044233701ISBN: 0-7695-2128-2 (print)OAI: oai:DiVA.org:kth-44315DiVA: diva2:451218
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

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Schüldt, Christian

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CiteExportLink to record
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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
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