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Euclidian Shape and Motion from Multiple Perspective Views by Affine Iterations

Stéphane Christy 1 Radu Horaud 
1 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 : In this paper we describe a method for solving the Euclidean reconstruction problem with a perspective camera model by incrementally performing an Euclidean reconstruction with either a weak or a para perspective camera model. With respect to other methods that compute shape and motion from a sequence of images with a calibrated perspective camera, this method converges in a few iterations, is computationnaly efficient, and does not suffer from the non linear nature of the problem. With respect to factorization and/or affine-invariant methods, this method solves for the sign (reversal) ambiguity in a very simple way and provides much more accurate reconstructions results. We give a detailed account of the method, analyse its convergence based on numerical and experimental considerations, and test its efficiency both with synthetic and real data.
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Submitted on : Wednesday, May 24, 2006 - 2:52:05 PM
Last modification on : Wednesday, May 4, 2022 - 12:12:03 PM
Long-term archiving on: : Tuesday, April 12, 2011 - 4:19:03 PM


  • HAL Id : inria-00074254, version 1



Stéphane Christy, Radu Horaud. Euclidian Shape and Motion from Multiple Perspective Views by Affine Iterations. RR-2421, INRIA. 1994. ⟨inria-00074254⟩



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