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Spatio-temporal Motion Tracking with Unsynchronized Cameras

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44378

Elhayek,  Ahmed
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45557

Stoll,  Carsten
Computer Graphics, MPI for Informatics, Max Planck Society;

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/persons44776

Kim,  Kwang In
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;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45610

Theobalt,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;

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Zitation

Elhayek, A., Stoll, C., Hasler, N., Kim, K. I., Seidel, H.-P., & Theobalt, C. (2012). Spatio-temporal Motion Tracking with Unsynchronized Cameras. In 2012 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1870-1877). Piscataway, NJ: IEEE. doi:10.1109/CVPR.2012.6247886.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0015-138D-B
Zusammenfassung
We present a new spatio-temporal method for markerless motion capture. We reconstruct the pose and motion of a character from a multi-view video sequence without requiring the cameras to be synchronized and without aligning captured frames in time. By formulating the model-to-image similarity measure as a temporally continuous functional, we are also able to reconstruct motion in much higher temporal detail than was possible with previous synchronized approaches. By purposefully running cameras unsynchronized we can capture even very fast motion at speeds that off-the-shelf but high quality cameras provide.