A Probabilistic Framework for Surface Reconstruction from Multiple Images

@inproceedings{Agrawal2001APF,
  title={A Probabilistic Framework for Surface Reconstruction from Multiple Images},
  author={Motilal Agrawal and Larry S. Davis},
  booktitle={CVPR},
  year={2001}
}
This paper presents a novel probabilistic framework for 3D surface reconstruction from multiple stereo images. The method works on a discrete voxelized representation of the scene. An iterative scheme is used to estimate the probability that a scene point lies on the true 3D surface. The novelty of our approach lies in the ability to model and recover surfaces which may be occluded in some views. This is done by explicitly estimating the probabilities that a 3D scene point is visible in a… CONTINUE READING
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References

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Showing 1-10 of 20 references

What do n photographs tell us about 3d shape. InProceedings

  • K. Kutulakos, S. Seitz
  • IEEE International Conference on Computer Vision…
  • 1999
Highly Influential
4 Excerpts

Volumetric scene reconstruction from multiple views

  • C. R. Dyer
  • Foundations of Image Analysis . Kluwer,
  • 2001
1 Excerpt

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