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Conference Paper

Markerless Motion Capture with Unsynchronized Moving Cameras

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44590

Hasler,  Nils
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45312

Rosenhahn,  Bodo
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45618

Thormählen,  Thorsten
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45695

Wand,  Michael
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44472

Gall,  Jürgen
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

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Citation

Hasler, N., Rosenhahn, B., Thormählen, T., Wand, M., Gall, J., & Seidel, H.-P. (2009). Markerless Motion Capture with Unsynchronized Moving Cameras. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009) (pp. 224-231). Washington DC, USA: IEEE Computer Society.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-19BB-0
Abstract
In this work we present an approach for markerless motion capture (MoCap) of articulated objects, which are recorded with multiple unsynchronized moving cameras. Instead of using fixed (and expensive) hardware synchronized cameras, this approach allows us to track people with off-the-shelf handheld video ca\-me\-ras. To prepare a sequence for motion capture, we first reconstruct the static background and the position of each camera using Structure-from-Motion (SfM). Then the cameras are registered to each other using the reconstructed static background geometry. Camera synchronization is achieved via the audio streams recorded by the ca\-me\-ras in parallel. Finally, a markerless MoCap approach is applied to recover positions and joint configurations of subjects. Feature tracks and dense background geometry are further used to stabilize the MoCap. The ex\-pe\-ri\-ments show examples with highly challenging indoor and outdoor scenes.