Human 3D Motion Computation from a Varying Number of Cameras

  • Magnus Burenius
  • Josephine Sullivan
  • Stefan Carlsson
  • Kjartan Halvorsen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6688)

Abstract

This paper focuses on how the accuracy of marker-less human motion capture is affected by the number of camera views used. Specifically, we compare the 3D reconstructions calculated from single and multiple cameras. We perform our experiments on data consisting of video from multiple cameras synchronized with ground truth 3D motion, obtained from a motion capture session with a professional footballer. The error is compared for the 3D reconstructions, of diverse motions, estimated using the manually located image joint positions from one, two or three cameras. We also present a new bundle adjustment procedure using regression splines to impose weak prior assumptions about human motion, temporal smoothness and joint angle limits, on the 3D reconstruction. The results show that even under close to ideal circumstances the monocular 3D reconstructions contain visual artifacts not present in the multiple view case, indicating accurate and efficient marker-less human motion capture requires multiple cameras.

Keywords

Motion Capture 3D Reconstruction Monocular Bundle Adjustment Regression Splines 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Magnus Burenius
    • 1
  • Josephine Sullivan
    • 1
  • Stefan Carlsson
    • 1
  • Kjartan Halvorsen
    • 1
  1. 1.KTH CSC/CVAPStockholmSweden

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