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Bundle Adjustment for Stereoscopic 3D

  • Christian Kurz
  • Thorsten Thormählen
  • Hans-Peter Seidel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6930)

Abstract

The recent resurgence of stereoscopic 3D films has triggered a high demand for post-processing tools for stereoscopic image sequences. Camera motion estimation, also known as structure-from-motion (SfM) or match-moving, is an essential step in the post-processing pipeline. In order to ensure a high accuracy of the estimated camera parameters, a bundle adjustment algorithm should be employed. We present a new stereo camera model for bundle adjustment. It is designed to be applicable to a wide range of cameras employed in today’s movie productions. In addition, we describe how the model can be integrated efficiently into the sparse bundle adjustment framework, enabling the processing of stereoscopic image sequences with traditional efficiency and improved accuracy. Our camera model is validated by synthetic experiments, on rendered sequences, and on a variety of real-world video sequences.

Keywords

Camera Model Stereo Camera Bundle Adjustment Visual Odometry Left Camera 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Christian Kurz
    • 1
  • Thorsten Thormählen
    • 1
  • Hans-Peter Seidel
    • 1
  1. 1.Max Planck Institute for Computer Science (MPII)SaarbrückenGermany

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