Iterative low complexity factorization for projective reconstruction

Authors:
Hanno Ackermann;Kenichi Kanatani
Affiliations:
Department of Computer Science, Okayama University, Okayama, Japan;Department of Computer Science, Okayama University, Okayama, Japan
Venue:
RobVis'08 Proceedings of the 2nd international conference on Robot vision
Year:
2008

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Abstract

We present a highly efficient method for estimating the structure and motion from image sequences taken by uncalibrated cameras. The basic principle is to do projective reconstruction first followed by Euclidean upgrading. However, the projective reconstruction step dominates the total computational time, because we need to solve eigenproblems of matrices whose size depends on the number of frames or feature points. In this paper, we present a new algorithm that yields the same solution using only matrices of constant size irrespective of the number of frames or points. We demonstrate the superior performance of our algorithm, using synthetic and real video images.