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Maximizing validity in 2D motion analysis
KTH, Tidigare Institutioner, Numerisk analys och datalogi, NADA.
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
2004 (engelsk)Inngår i: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2 / [ed] Kittler, J; Petrou, M; Nixon, M, 2004, s. 179-183Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Classifying and analyzing human motion from a video is relatively common in many areas. Since the motion is carried out in 3D space, the 2D projection provided by a video is somewhat limiting. The question we are investigating in this article is how much information is actually lost when going from 3D to 2D and how this information loss depends on factors, such as viewpoint and tracking errors that inevitably will occur if the 2D sequences are analysed automatically.

sted, utgiver, år, opplag, sider
2004. s. 179-183
Serie
INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, ISSN 1051-4651
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-44313DOI: 10.1109/ICPR.2004.1334090ISI: 000223877400043Scopus ID: 2-s2.0-10044224484ISBN: 0-7695-2128-2 (tryckt)OAI: oai:DiVA.org:kth-44313DiVA, id: diva2:451223
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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