  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 parameterless 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.
