Skip to Main content Skip to Navigation
New interface
Journal articles

Euclidean Shape and Motion from Multiple Perspective Views by Affine Iterations

Stéphane Christy 1 Radu Horaud 1, 2 
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 Euclidean reconstruction with either a weak or a paraperspective 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 computationally efficient, and does not suffer from the non linear nature of the problem. With respect to methods that use an affine camera model (such as factorization) the method described below 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, analyze its convergence based on numerical and experimental considerations, and test its efficiency with both synthetic and real data.
Document type :
Journal articles
Complete list of metadata
Contributor : Perception team Connect in order to contact the contributor
Submitted on : Tuesday, May 3, 2011 - 9:14:36 AM
Last modification on : Wednesday, May 4, 2022 - 12:12:03 PM
Long-term archiving on: : Thursday, August 4, 2011 - 2:45:52 AM


Files produced by the author(s)




Stéphane Christy, Radu Horaud. Euclidean Shape and Motion from Multiple Perspective Views by Affine Iterations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18 (11), pp.1098--1104. ⟨10.1109/34.544079⟩. ⟨inria-00590057⟩



Record views


Files downloads