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Euclidean and Affine Structure/Motion for Uncalibrated Cameras from Affine Shape and Subsidiary Information

  • Gunnar Sparr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1506)

Abstract

The paper deals with the structure-motion problem for uncalibrated cameras, in the case that subsidiary information is available, consisting e.g. in known coplanarities or parallelities among points in the scene, or known positions of some focal points (hand-eye calibration). Despite unknown camera calibrations, it is shown that in many instances the subsidiary information makes affine or even Euclidean reconstruction possible. A parametrization by affine shape and depth is used, providing a simple framework for the incorporation of apriori knowledge, and enabling the development of iterative, rapidly converging algorithms. Any number of points in any number of images are used in a uniform way, with equal priority, and independently of coordinate representations. Moreover, occlusions are allowed.

Keywords

Linear Subspace Shape Space Proximity Measure Parallel Projection Projective Reconstruction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Gunnar Sparr
    • 1
  1. 1.Dept. of MathematicsLund University/LTHLundSweden

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