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
Local descriptors for spatio-temporal recognition
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0002-9081-2170
2006 (English)In: Spatial Coherence For Visual Motion Analysis: First International Workshop, SCVMA 2004, Prague, Czech Republic, May 15, 2004. Revised Papers / [ed] MacLean, WJ, Springer Berlin/Heidelberg, 2006, Vol. 3667, 91-103 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents and investigates a set of local space-time descriptors for representing and recognizing motion patterns in video. Following the idea of local features in the spatial domain, we use the notion of space-time interest points and represent video data in terms of local space-time events. To describe such events, we define several types of image descriptors over local spatio-temporal neighborhoods and evaluate these descriptors in the context of recognizing human activities. In particular, we compare motion representations in terms of spatio-temporal jets, position dependent histograms, position independent histograms, and principal component analysis computed for either spatio-temporal gradients or optic flow. An experimental evaluation on a video database with human actions shows that high classification performance can be achieved, and that there is a clear advantage of using local position dependent histograms, consistent with previously reported findings regarding spatial recognition.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2006. Vol. 3667, 91-103 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 3667
Keyword [en]
Human Movement, Representation
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-41720DOI: 10.1007/11676959_8ISI: 000237244700008Scopus ID: 2-s2.0-33745757308ISBN: 3-540-32533-6 (print)OAI: oai:DiVA.org:kth-41720DiVA: diva2:445261
Conference
1st International Workshop on Spatial Coherence for Visual Motion Analysis, SCVMA 2004; Prague; 15 May 2004 through 15 May 2004
Note

QC 20111003

Available from: 2013-04-22 Created: 2011-09-30 Last updated: 2013-04-22Bibliographically approved

Open Access in DiVA

fulltext(757 kB)806 downloads
File information
File name FULLTEXT01.pdfFile size 757 kBChecksum SHA-512
b7c17d550f5058e4e98e3ed67fd658d6ee622155cab1075107189d385c2db978752795031cffcc48b2414ccb4ca0847b3fe5e3a0f485db31a269284fcedabb17
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusThe final publication is available at www.springerlink.com

Authority records BETA

Lindeberg, Tony

Search in DiVA

By author/editor
Laptev, IvanLindeberg, Tony
By organisation
Computer Vision and Active Perception, CVAP
Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 806 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 444 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