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Recognizing human actions: A local SVM approach
KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.ORCID-id: 0000-0003-3439-0468
KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
2004 (engelsk)Inngår i: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3 / [ed] Kittler, J; Petrou, M; Nixon, M, 2004, s. 32-36Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
2004. s. 32-36
Serie
INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, ISSN 1051-4651
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-44315DOI: 10.1109/ICPR.2004.1334462ISI: 000223879500009Scopus ID: 2-s2.0-10044233701ISBN: 0-7695-2128-2 (tryckt)OAI: oai:DiVA.org:kth-44315DiVA, id: diva2:451218
Konferanse
17th International Conference on Pattern Recognition (ICPR) Location: British Machine Vis Assoc, Cambridge, ENGLAND Date: AUG 23-26, 2004
Merknad
QC 20111025Tilgjengelig fra: 2011-10-25 Laget: 2011-10-20 Sist oppdatert: 2018-01-12bibliografisk kontrollert

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