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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.
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
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.
Baumberg, A., 2000. Reliable feature matching across widely
separated views, Computer Vision & Pattern Recognition
(CVPR) 2000, pp. 774-781.
Fischler, M.A. and Bolles, R.C., 1981. Random sample consensus: a
paradigm for model fitting with applications to image analysis
and automated cartography. Communications of the ACM, Vol.
24(6), pp. 381-395.
Fórstner, W., 2000. New orientation procedures. International
Archives of Photogrammetry and Remote Sensing, Vol. 33 part
3, pp. 297-304.
Fórstner, W. and Gülch, E., 1999. Automatic orientation and
recognition in highly structured scenes. J. of Photo-grammetry
and Remote Sensing, Vol. 54, pp. 23-34.
Habib, A. and Kelley, D., 2001. Automatic relative orientation of
large scale imager over urban areas using modified iterated
Hough transform. J. of Photogrammetry and Remote Sensing,
Vol. 56, pp. 29-41.
Heipke, C., 1997. Automation of interior, relative, and absolute
orientation. ISPRS J. of Photogrammetry and Remote Sensing,
Vol. 52, pp. 1-19.
Matas, J., Urban, M. and Pajdla, T., 2001. Unifying view for wide-
baseline stereo matching. In: B. Likar (Editor), Computer Vision
Winter Workshop. Slovenian Pattern Recorgnition Society, pp.
Pollefeys, M., Koch, R., Vergauwen, M. and Van Gool, L., 2000.
Automated reconstruction of 3D scenes from sequences of
images. ISPRS J. of Photogrammetry and Remote Sensing, Vol.
55(4), pp. 251-267.
Pritchett, P. and Zisserman, A., 1998. Wide baseline stereo matching,
Sixth International Conference on Computer Vision, pp. 754 -
Teller, S., 2001. Scalable, controlled imagery capture in urban
environments. Report 825, MIT Laboratory for Computer
Tuytelaars, T. and Van Gool, L., 2000. Wide Baseline Stereo
Matching based on Local, Affinely Invariant Regions, British
Machine Vision Conference BMVC'2000, pp. 412-425.
van den Heuvel, F.A., 1998. Vanishing point detection for
architectural photogrammetry. In: H. Chikatsu and E. Shimizu
(Editors). International Archives of Photogrammetry and
Remote Sensing, Vol. 32 part 5, pp. 652-659.
van den Heuvel, F.A., 1999. Estimation of interior orientation
parameters from constraints on line measurements in a single
image. In: P. Patias (Editor). International Archives of
Photogrammetry and Remote Sensing, Vol. 32 part SW11, pp.
van den Heuvel, F.A., 2001. Object reconstruction from a single
architectural image taken with an uncalibrated camera.
Photogrammetrie, Fernerkundung, Geoinformation, Vol.
2001(4), pp. 247-260.
Wang, Y., 1998. Principles and applications of structural image
matching. ISPRS J. of Photogrammetry and Remote Sensing,
Vol. 53, pp. 154-165.

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