BMVC 2004, Kingston, 7th-9th Sept, 2004

Constraints on perspective images and circular panoramas
M. Menem and T. Pajdla (Czech Technical University, Prague)

We describe an algebraic constraint on corresponding image points in a perspective
image and a circular panorama and provide a method to estimate
it from noisy image measurements. Studying this combination of cameras
is a step forward in localization and recognition since a database of circular
panoramas captures completely the appearance of objects and scenes, and
perspective images are the simplest query images. The constraint gives a way
to use a RANSAC-like algorithm for image matching. We introduce a general
method to establish constraints between (non-central) images in the form
of a bilinear function of the lifted coordinates of corresponding image points.
We apply the method to obtain an algebraic constraint for a perspective image
and a circular panorama. The algebraic constraints are interpreted geometrically
and the constraints estimated from image data are used to auto-calibrate
cameras and to compute a metric reconstruction of the scene observed. A
synthetic experiment demonstrates that the proposed reconstruction method
behaves favorably in presence of image noise. As a proof of concept, the
constraints are estimated from real images of indoor scenes and used to reconstruct
positions of cameras and to compute a metric reconstruction of the
(pdf article)