Markerless Motion Capture with unsynchronized moving cameras

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...

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Published in2009 IEEE Conference on Computer Vision and Pattern Recognition pp. 224 - 231
Main Authors Hasler, Nils, Rosenhahn, Bodo, Thormahlen, Thorsten, Wand, Michael, Gall, Juergen, Seidel, Hans-Peter
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2009
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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 cameras. 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 cameras 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 experiments show examples with highly challenging indoor and outdoor scenes.
AbstractList 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 cameras. 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 cameras 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 experiments show examples with highly challenging indoor and outdoor scenes.
Author Hasler, Nils
Seidel, Hans-Peter
Gall, Juergen
Thormahlen, Thorsten
Rosenhahn, Bodo
Wand, Michael
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Snippet In this work we present an approach for markerless motion capture (MoCap) of articulated objects, which are recorded with multiple unsynchronized moving...
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StartPage 224
SubjectTerms Cameras
Computer graphics
Computer vision
Geometry
Hardware
Humans
Image reconstruction
Layout
Streaming media
Surface reconstruction
Title Markerless Motion Capture with unsynchronized moving cameras
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