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3D pictorial structures for multiple view articulated pose estimation
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.
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
2013 (English)In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society, 2013, 3618-3625 p.Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of automatically estimating the 3D pose of humans from images, taken from multiple calibrated views. We show that it is possible and tractable to extend the pictorial structures framework, popular for 2D pose estimation, to 3D. We discuss how to use this framework to impose view, skeleton, joint angle and intersection constraints in 3D. The 3D pictorial structures are evaluated on multiple view data from a professional football game. The evaluation is focused on computational tractability, but we also demonstrate how a simple 2D part detector can be plugged into the framework.

Place, publisher, year, edition, pages
IEEE Computer Society, 2013. 3618-3625 p.
Series
IEEE Conference on Computer Vision and Pattern Recognition. Proceedings, ISSN 1063-6919
Keyword [en]
human pose estimation, motion capture, multiple view 3D reconstruction, part-based models, pictorial structures
National Category
Engineering and Technology Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-129706DOI: 10.1109/CVPR.2013.464ISI: 000331094303088Scopus ID: 2-s2.0-84887329445OAI: oai:DiVA.org:kth-129706DiVA: diva2:653207
Conference
26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013; Portland, OR; United States; 23 June 2013 through 28 June 2013
Note

QC 20131007

Available from: 2013-10-03 Created: 2013-10-03 Last updated: 2014-03-24Bibliographically approved
In thesis
1. Human 3D Pose Estimation in the Wild: using Geometrical Models and Pictorial Structures
Open this publication in new window or tab >>Human 3D Pose Estimation in the Wild: using Geometrical Models and Pictorial Structures
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. viii, 178 p.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2013:15
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:kth:diva-138136 (URN)978-91-7501-980-2 (ISBN)
Public defence
2014-01-21, F3, KTH, Lindstedtsvägen 26, Stockholm, 13:00
Opponent
Supervisors
Note

QC 20131218

Available from: 2013-12-18 Created: 2013-12-18 Last updated: 2013-12-18Bibliographically approved

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Citation style
  • apa
  • harvard1
  • ieee
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  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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