\subsection*{\centering Abstract}

Given two arbitrary views of a scene  under
central projection, if the motion of points on a parametric surface
is compensated, the residual 
parallax displacement field on the reference image is an epipolar field.
The parallax magnitude at a point, after suitable scaling, is
an affine invariant; if the surface aligned is a plane, it is
directly proportional to
the height of the point from the plane and inversely proportional to
its depth from the camera.
We exploit the above result to infer 3D height information 
from {\it oblique} aerial 2D images.  We use
direct methods to register the  aerial images,
develop methods to infer height information under the following
three conditions: (i) focal length and image center are both known,
(ii) only the focal length is known, and
(iii) both are unknown.  We use the invariance property of the scaled parallax
magnitudes to combine multiple frame information to obtain accurate heights,
and to extrapolate new views from a given set of views (i.e., in
photogrammetric terms, to achieve ``transfer'').  We use the view extrapolation
process to construct a panoramic mosaic image by combining multiple views that
is accurate in terms of 3D positions of surfaces.





