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1                       Calibration, point matches, and line segment matches
2                             of a close-range architectural image set
3                       ----------------------------------------------------
4
5This set contains images of an Oxford University building, taken by
6Olympus C-820L digital camera. The camera was held by a person
7standing on the ground. The following was applied to the set:
8
91. Automated wide baseline stereo: affine & scale invariant features
10were detected in each image and matched by RANSAC, yielding projective
11camera matrices and a cloud of projective 3D points.
12
132. Metric upgrade from vanishing points: vanishing points computed
14from detected line segments and (along with square pixels assumption)
15used to upgrade the projective reconstruction to metric one.
16
173. Automated line segment matching: the line segments matched and
18reconstructed, using geometrical constraints on lines and photommetric
19information in their neighborhood.
20   There are some mismatches among the matched lines, mainly due to
21ill conditioning of the geometry for horizontal lines (because camera
22centers all lie in about horizontal plane).
23
24
25References:
26
271. Werner, T. and Zisserman, A.
28   New Techniques for Automated Architecture Reconstruction from Photographs
29   Proc. 7th European Conference on Computer Vision, Copenhagen, Denmark, 2002.
30   http://www.robots.ox.ac.uk/~vgg/publications/papers/werner02.{pdf,ps.gz}.
31
322. Werner, T. and Zisserman, A.
33   Model Selection for Automated Architectural Reconstruction from Multiple Views
34   Proc. British Machine Vision Conference, 2002.
35   http://www.robots.ox.ac.uk/~vgg/publications/papers/werner02a.{pdf,ps.gz}.
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