In this paper we present a new method for single image orientation
using an orthographic drawing or map of the scene. Environments which are
dominated by man made objects, such as industrial facilities or urban scenes,
are very rich of vertical and horizontal structures. These scene
constraints reflect in symbols in an associated drawing.
For example, vertical lines in the scene are usually marked as points
in a drawing. The resulting orientation may be used in augmented reality
systems or for initiating a subsequent bundle adjustment of all available images.
In this paper we propose to use such scene constraints taken from a
drawing to estimate the camera orientation. We use observed vertical lines,
horizontal lines, and points to estimate the projection matrix P of the image.
We describe the constraints in terms of projective geometry
which makes them straightforward and very transparent. In contrast to
the work of Bondyfalatetal 2001, we give a direct solution for P
without using the fundamental matrix between image and map as we do not
need parallelity constraints between lines in a vertical plane other than for
horizontal lines, nor observed perpendicular lines.
We present both a direct solution for P and a statistically optimal,
iterative solution, which takes the uncertainties of the contraints and the
observations in the image and the drawing into account. It is a simplifying
modification of the eigenvalue method of Matei/Meer 1997. The method allows to
evaluate the results statistically, namely to verify the used projection model
and the assumed statistical properties of the measured image and map quantities
and to validate the achieved accuracy of the estimated projection matrix P.
To demonstrate the feasibility of the approach, we present results of the application
of our method to both synthetic data and real scenes in industrial environment.
Statistical tests show the performance and prove the rigour of the new method.