PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Reconstructing camera projection matrices from multiple pairwise overlapping views
Jacob Goldberger
Computer Vision and Image Understanding Volume 97, Number 3, pp. 283-296, 2005.


In this work we address the problem of projective reconstruction from multiple views with missing data. Factorization based algorithms require point correspondences across all the views. In many applications this is an unrealistic assumption. Current methods that solve the problem of projective reconstruction with missing data require correspondence information across triplets of images. We propose a projective reconstruction method that yields a consistent camera set given the fundamental matrices between pairs of views without directly using the image correspondences. The algorithm is based on breaking the reconstruction problem into small steps. In each step, we eliminate as much uncertainty as possible.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
ID Code:1571
Deposited By:Jacob Goldberger
Deposited On:28 November 2005