ML Anthology

Reconstruction with Interval Constraints Propagation

Michela Farenzena, Andrea Fusiello, Agostino Dovier
CVPR 2006 pp. 1185-1190
doi:10.1109/CVPR.2006.246 /cvpr/2006/farenzena2006cvpr-reconstruction/

Abstract

In this paper we demonstrate how Interval Analysis and Constraint Logic Programming can be used to obtain an accurate geometric model of a scene that rigorously takes into account the propagation of data errors and roundoff. Image points are represented as small rectangles: As a result, the output of the n-views triangulation is not a single point in space, but a polyhedron that contains all the possible solutions. Interval Analysis is used to bound this polyhedron with a box. Geometrical constraints such as orthogonality, parallelism, and coplanarity are subsequently enforced in order to reduce the size of those boxes, using Constraint Logic Programming. Experiments with real calibrated images illustrate the approach

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Cite

Text

Farenzena et al. "Reconstruction with Interval Constraints Propagation." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2006. doi:10.1109/CVPR.2006.246

Markdown

[Farenzena et al. "Reconstruction with Interval Constraints Propagation." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2006.](https://mlanthology.org/cvpr/2006/farenzena2006cvpr-reconstruction/) doi:10.1109/CVPR.2006.246

BibTeX

@inproceedings{farenzena2006cvpr-reconstruction,
  title     = {{Reconstruction with Interval Constraints Propagation}},
  author    = {Farenzena, Michela and Fusiello, Andrea and Dovier, Agostino},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2006},
  pages     = {1185-1190},
  doi       = {10.1109/CVPR.2006.246},
  url       = {https://mlanthology.org/cvpr/2006/farenzena2006cvpr-reconstruction/}
}