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Motion Capture from Dynamic Orthographic Cameras
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.
2011 (English)In: 4DMOD - 1st IEEE Workshop on Dynamic Shape Capture and Analysis, 2011Conference paper, Published paper (Refereed)
Abstract [en]

We present an extension to the scaled orthographic camera model. It deals with dynamic cameras looking at faraway objects. The camera is allowed to change focal lengthand translate and rotate in 3D. The model we derive saysthat this motion can be treated as scaling, translation androtation in a 2D image plane. It is valid if the camera and itstarget move around in two separate regions that are smallcompared to the distance between them.We show two applications of this model to motion capture applications at large distances, i.e. outside a studio,using the affine factorization algorithm. The model is usedto motivate theoretically why the factorization can be carried out in a single batch step, when having both dynamiccameras and a dynamic object. Furthermore, the model isused to motivate how the position of the object can be reconstructed by measuring the virtual 2D motion of the cameras. For testing we use videos from a real football gameand reconstruct the 3D motion of a footballer as he scoresa goal.

Place, publisher, year, edition, pages
2011.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-51110DOI: 10.1109/ICCVW.2011.6130445ISI: 000300056700231Scopus ID: 2-s2.0-84856626223OAI: oai:DiVA.org:kth-51110DiVA: diva2:463415
Conference
4DMOD - 1st IEEE Workshop on Dynamic Shape Capture and Analysis. Barcelona, Spain. 2011-11-13.
Note

QC 20111213

Available from: 2011-12-09 Created: 2011-12-09 Last updated: 2013-12-18Bibliographically 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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Publisher's full textScopushttp://www.csc.kth.se/~burenius/Burenius4DMOD2011.pdf

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