TR2013-110

Lifting 3D Manhattan Lines from a Single Image


    •  Ramalingam, S., Brand, M., "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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  • Research Area:

    Computer Vision

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.