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Maximizing validity in 2D motion analysis
KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
2004 (English)In: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2 / [ed] Kittler, J; Petrou, M; Nixon, M, 2004, 179-183 p.Conference paper (Refereed)
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.

Place, publisher, year, edition, pages
2004. 179-183 p.
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-44313DOI: 10.1109/ICPR.2004.1334090ISI: 000223877400043ScopusID: 2-s2.0-10044224484ISBN: 0-7695-2128-2OAI: diva2:451223
17th International Conference on Pattern Recognition (ICPR) Location: British Machine Vis Assoc, Cambridge, ENGLAND Date: AUG 23-26, 2004
QC 20111025Available from: 2011-10-25 Created: 2011-10-20 Last updated: 2012-01-20Bibliographically approved

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Eriksson, MartinCarlsson, Stefan
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