TR2013-110
Lifting 3D Manhattan Lines from a Single Image
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- "Lifting 3D Manhattan Lines from a Single Image", IEEE International Conference on Computer Vision (ICCV), December 2013.BibTeX TR2013-110 PDF
- @inproceedings{Ramalingam2013dec,
- author = {Ramalingam, S. and Brand, M.},
- title = {{Lifting 3D Manhattan Lines from a Single Image}},
- booktitle = {IEEE International Conference on Computer Vision (ICCV)},
- year = 2013,
- month = dec,
- url = {https://www.merl.com/publications/TR2013-110}
- }
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- "Lifting 3D Manhattan Lines from a Single Image", IEEE International Conference on Computer Vision (ICCV), December 2013.
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Abstract:
We propose a novel and an efficient method for reconstructing the 3D arrangement of lines extracted from a single image, using vanishing points, orthogonal structure, and an optimization procedure that considers all plausible connectivity constraints between lines. Line detection identifies a large number of salient lines that intersect or nearly intersect in an image, but relatively a few of these apparent junctions correspond to real intersections in the 3D scene. We use linear programming (LP) to identify a minimal set of least-violated connectivity constraints that are sufficient to unambiguously reconstruct the 3D lines. In contrast to prior solutions that primarily focused on well-behaved synthetic line drawings with severely restricting assumptions, we develop an algorithm that can work on real images. The algorithm produces line reconstruction by identifying 95% correct connectivity constraints in York Urban database, with a total computation time of 1 second per image.