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Title
Close-range imaging, long-range vision


building), the overall Fisher-test is often rejected, while all
tests of individual correspondences are accepted. The lack of
"perfect" correspondences reduces the precision that can be
reached. To check this precision, relative orientation of both
pairs was determined through least-squares adjustment of 20
manually measured points. The deviations in the orientation
of the detected epipole are below 2 degree (Table 2). As
expected the computational burden of the proposed method is
considerable. For the first pair computational time is in the
order of 10 minutes on a modern PC.






Figure 7: The detected correspondences of both pairs.
5. CONCLUSIONS
A new method for automatic relative orientation has been
presented. It relies on the extraction of straight image lines
and their vanishing point labelling. Vanishing point detection
is a crucial step in the procedure that results in an ambiguous
orientation of the images relative to the building. The epipole
detection shows many similarities with the vanishing point
—232—
detection. Both are based on clustering of rigorous statistical
tests and adjustment of constraints on the observations.
Experiments show that relative orientation can be detected
successfully between two images with an angle of 65 degree
between the optical axes (see section 4, first image pair),
while the difference in orientation with a manually
determined relative position vector was less than 2 degree.
The proposed method can be regarded as a first step towards
automated reconstruction because the model coordinates of
the corresponding points and the parameters of the plane in
which they recede become available as a by-product.
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