TITLE: Wide Area Multiple Camera Calibration and Estimation of Radial Distortion

AUTHORS: Joao P. Barreto
GRASP Laboratory, University of Pennsylvania,
Philadelphia PA, 19104
and
ISR/DEEC, University of Coimbra,
Coimbra, Portugal

Kostas Daniilidis
GRASP Laboratory, University of Pennsylvania,
Philadelphia PA, 19104

ABSTRACT:

The calibration of cameras distributed in a wide area is a
challenging task because it is impossible to use reference objects
visible to all cameras and because wide field-of-view cameras suffer
under radial distortion. The present work proposes the first algorithm
in the literature for radial distortion estimation from multiple views
without involving non-linear minimization. The correspondences between
views are obtained by deliberately moving an LED in thousands of unknown
positions in front of the cameras. Then both projection matrices and
radial distortion parameters are simultaneously computed using
a factorization approach. The algorithm is based on the
application of two subspace approximation steps. At these steps, the
estimated approximate solution for a matrix can be projected to the
manifold of the parameter space by adjusting the singular values.
It is remarkable, that our system does not involve a single non-linear
minimization or outlier treatment and still produces accurate results
which have been tested in a multi-camera reconstruction algorithm. In
addition to real imagery results, we have analyzed the behavior of the
algorithm in simulations.


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