Covariance Propagation and Next Best View Planning for 3D Reconstruction

Sebastian Haner and Anders Heyden

Abstract. This paper examines the potential benefits of applying next best view planning to sequential 3D reconstruction from unordered image sequences. A standard sequential structure-and-motion pipeline is extended with active selection of the order in which cameras are resectioned. To this end, approximate covariance propagation is implemented throughout the system, providing running estimates of the uncertainties of the reconstruction, while also enhancing robustness and accuracy. Experiments show that the use of expensive global bundle adjustment can be reduced throughout the process, while the additional cost of propagation is essentially linear in the problem size.

Keywords: Structure and motion, covariance propagation, next best view planning

LNCS 7573, p. 545 ff.

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