Learning epipolar geometry from image sequences
Yonatan Wexler, Andrew W. Fitzgibbon and Andrew Zisserman
Abstract:
We wish to determine the epipolar geometry of a stereo camera pair
from image measurements alone. This paper describes a solution to this
problem which does not require a parametric model of the camera
system, and consequently applies equally well to a wide class of
stereo configurations. Examples in the paper range from a standard
pinhole stereo configuration to more exotic systems combining curved
mirrors and wide-angle lenses. The method described here allows
epipolar curves to be learned from multiple image pairs presented to
the stereo cameras. By aggregating information over the multiple
images, a dense map of the epipolar curves can be determined on the
images. The algorithm requires a large number of images, but has the
distinct benefit that the correspondence problem does not have to be
explicitly solved. We show that for standard stereo configurations the
results are comparable to those obtained from a state of the art
parametric model method, despite the significantly weaker constraints
on the non-parametric model. The new algorithm is simple to implement,
so it may easily be employed on a new and possibly complex camera
system.
Paper: pdf
Last modified: Sun May 18 10:31:21 2003