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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.