International Journal of Computer Vision

, Volume 66, Issue 3, pp 305–317 | Cite as

Projective Reconstruction from Multiple Views with Minimization of 2D Reprojection Error

  • Y. S. Hung
  • W. K. Tang


The problem of projective reconstruction by minimization of the 2D reprojection error in multiple images is considered. Although bundle adjustment techniques can be used to minimize the 2D reprojection error, these methods being based on nonlinear optimization algorithms require a good starting point. Quasi-linear algorithms with better global convergence properties can be used to generate an initial solution before submitting it to bundle adjustment for refinement. In this paper, we propose a factorization-based method to integrate the initial search as well as the bundle adjustment into a single algorithm consisting of a sequence of weighted least-squares problems, in which a control parameter is initially set to a relaxed state to allow the search of a good initial solution, and subsequently tightened up to force the final solution to approach a minimum point of the 2D reprojection error. The proposed algorithm is guaranteed to converge. Our method readily handles images with missing points.


multiple views projective reconstruction structure and motion sub-space method factorization method projective bundle adjustment 


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Copyright information

© Springer Science + Business Media, Inc. 2006

Authors and Affiliations

  1. 1.Department of Electrical and Electronic EngineeringThe University of Hong KongHong Kong

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