[37] | 1 | Calibration, point matches, and line segment matches |
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| 2 | of a close-range architectural image set |
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| 3 | ---------------------------------------------------- |
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| 4 | |
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| 5 | This set contains images of an Oxford University building, taken by |
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| 6 | Olympus C-820L digital camera. The camera was held by a person |
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| 7 | standing on the ground. The following was applied to the set: |
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| 8 | |
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| 9 | 1. Automated wide baseline stereo: affine & scale invariant features |
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| 10 | were detected in each image and matched by RANSAC, yielding projective |
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| 11 | camera matrices and a cloud of projective 3D points. |
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| 12 | |
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| 13 | 2. Metric upgrade from vanishing points: vanishing points computed |
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| 14 | from detected line segments and (along with square pixels assumption) |
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| 15 | used to upgrade the projective reconstruction to metric one. |
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| 16 | |
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| 17 | 3. Automated line segment matching: the line segments matched and |
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| 18 | reconstructed, using geometrical constraints on lines and photommetric |
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| 19 | information in their neighborhood. |
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| 20 | There are some mismatches among the matched lines, mainly due to |
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| 21 | ill conditioning of the geometry for horizontal lines (because camera |
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| 22 | centers all lie in about horizontal plane). |
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| 23 | |
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| 24 | |
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| 25 | References: |
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| 26 | |
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| 27 | 1. Werner, T. and Zisserman, A. |
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| 28 | New Techniques for Automated Architecture Reconstruction from Photographs |
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| 29 | Proc. 7th European Conference on Computer Vision, Copenhagen, Denmark, 2002. |
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| 30 | http://www.robots.ox.ac.uk/~vgg/publications/papers/werner02.{pdf,ps.gz}. |
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| 31 | |
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| 32 | 2. Werner, T. and Zisserman, A. |
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| 33 | Model Selection for Automated Architectural Reconstruction from Multiple Views |
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| 34 | Proc. British Machine Vision Conference, 2002. |
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| 35 | http://www.robots.ox.ac.uk/~vgg/publications/papers/werner02a.{pdf,ps.gz}. |
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