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Camera Network Calibration and Synchronization from Silhouettes in Archived Video

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Abstract

In this paper we present an automatic method for calibrating a network of cameras that works by analyzing only the motion of silhouettes in the multiple video streams. This is particularly useful for automatic reconstruction of a dynamic event using a camera network in a situation where pre-calibration of the cameras is impractical or even impossible. The key contribution of this work is a RANSAC-based algorithm that simultaneously computes the epipolar geometry and synchronization of a pair of cameras only from the motion of silhouettes in video.

Our approach involves first independently computing the fundamental matrix and synchronization for multiple pairs of cameras in the network. In the next stage the calibration and synchronization for the complete network is recovered from the pairwise information. Finally, a visual-hull algorithm is used to reconstruct the shape of the dynamic object from its silhouettes in video. For unsynchronized video streams with sub-frame temporal offsets, we interpolate silhouettes between successive frames to get more accurate visual hulls. We show the effectiveness of our method by remotely calibrating several different indoor camera networks from archived video streams.

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Author notes

  1. Sudipta N. Sinha

    Present address: Microsoft Research, Redmond, USA

  2. Marc Pollefeys

    Present address: Institute of Computational Science, ETH Zurich, Zurich, Switzerland

Authors and Affiliations

  1. Department of Computer Science, UNC Chapel Hill, Chapel Hill, NC, USA

    Sudipta N. Sinha & Marc Pollefeys

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  1. Sudipta N. Sinha
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  2. Marc Pollefeys
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Correspondence to Sudipta N. Sinha.

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Sinha, S.N., Pollefeys, M. Camera Network Calibration and Synchronization from Silhouettes in Archived Video. Int J Comput Vis 87, 266–283 (2010). https://doi.org/10.1007/s11263-009-0269-2

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  • DOI: https://doi.org/10.1007/s11263-009-0269-2

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