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Euclidean Constraints for Uncalibrated Reconstruction

Boubakeur Boufama 1 Roger Mohr 1, 2 Françoise Veillon 1 
2 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : It is possible to recover the three-dimensional structure of a scene using images taken with uncalibrated cameras and pixel correspondences betweeen these images. But such reconstruction can only be performed up to a projective transformation of the 3-D space. Therefore, constraints have to be put on the reconstructed data to get the reconstruction in the Euclidean space. Such constraints arise from knowledge of the scene, such as the location of points, geometrical constraints on lines, etc. The kind of constraints that have to be added are discussed, and it is shown how they can be fed in a general framework. Experimental results on real data prove the feasibility, and experiments on simulated data address the accuracy of the results.
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Boubakeur Boufama, Roger Mohr, Françoise Veillon. Euclidean Constraints for Uncalibrated Reconstruction. 4th International Conference on Computer Vision (ICCV '93), May 1993, Berlin, Germany. pp.466--470, ⟨10.1109/ICCV.1993.378179⟩. ⟨inria-00548429⟩



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