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Conference Papers Year : 2017

Line-based Robust SfM with Little Image Overlap

Abstract

Usual Structure-from-Motion (SfM) techniques require at least trifocal overlaps to calibrate cameras and reconstruct a scene. We consider here scenarios of reduced image sets with little overlap, possibly as low as two images at most seeing the same part of the scene. We propose a new method, based on line coplanarity hypotheses, for estimating the relative scale of two independent bifocal calibrations sharing a camera, without the need of any trifocal information or Manhattan-world assumption. We use it to compute SfM in a chain of up-to-scale relative motions. For accuracy, we however also make use of trifocal information for line and/or point features, when present, relaxing usual trifocal constraints. For robustness to wrong assumptions and mismatches, we embed all constraints in a parameter-less RANSAC-like approach. Experiments show that we can calibrate datasets that previously could not, and that this wider applicability does not come at the cost of inaccuracy.
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Dates and versions

hal-01618686 , version 1 (18-10-2017)

Identifiers

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Yohann Salaün, Renaud Marlet, Pascal Monasse. Line-based Robust SfM with Little Image Overlap. 3DV 2017 International Conference on 3D Vision 2017, Oct 2017, Qingdao, China. ⟨10.1109/3DV.2017.00031⟩. ⟨hal-01618686⟩
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