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Tracking-as-recognition for articulated full-body human motion analysis

Peursum, Patrick, Venkatesh, Svetha and West, Geoff 2007, Tracking-as-recognition for articulated full-body human motion analysis, in CVPR 2007 : Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE, [Piscataway, N.J.], pp. [1]-[8], doi: 10.1109/CVPR.2007.383130.

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Title Tracking-as-recognition for articulated full-body human motion analysis
Author(s) Peursum, Patrick
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
West, Geoff
Conference name Computer Vision and Pattern Recognition. Conference (2007 : Minneapolis, Minn.)
Conference location Minneapolis, MN
Conference dates 17-22 Jun. 2007
Title of proceedings CVPR 2007 : Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Editor(s) [Unknown]
Publication date 2007
Conference series Computer Vision and Pattern Recognition. Conference
Start page [1]
End page [8]
Total pages 8
Publisher IEEE
Place of publication [Piscataway, N.J.]
Keyword(s) annealing
biological system modeling
costs
hidden Markov models
humans
layout
motion analysis
particle filters
particle tracking
testing
Summary This paper addresses the problem of markerless tracking of a human in full 3D with a high-dimensional (29D) body model Most work in this area has been focused on achieving accurate tracking in order to replace marker-based motion capture, but do so at the cost of relying on relatively clean observing conditions. This paper takes a different perspective, proposing a body-tracking model that is explicitly designed to handle real-world conditions such as occlusions by scene objects, failure recovery, long-term tracking, auto-initialisation, generalisation to different people and integration with action recognition. To achieve these goals, an action's motions are modelled with a variant of the hierarchical hidden Markov model The model is quantitatively evaluated with several tests, including comparison to the annealed particle filter, tracking different people and tracking with a reduced resolution and frame rate.
ISBN 9781424411801
1424411807
Language eng
DOI 10.1109/CVPR.2007.383130
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2007, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044592

Document type: Conference Paper
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.