  Low-frequency long-range errors (drift) are an endemic problem in 3D
structure from motion, and can often hamper reasonable reconstructions of the
scene. In this paper, we present a method to dramatically reduce scale and
positional drift by using extended structural features such as planes and
vanishing points. Unlike traditional feature matches, our extended features are
able to span non-overlapping input images, and hence provide long-range
constraints on the scale and shape of the reconstruction. We add these features
as additional constraints to a state-of-the-art global structure from motion
algorithm and demonstrate that the added constraints enable the reconstruction
of particularly drift-prone sequences such as long, low field-of-view videos
without inertial measurements. Additionally, we provide an analysis of the
drift-reducing capabilities of these constraints by evaluating on a synthetic
dataset. Our structural features are able to significantly reduce drift for
scenes that contain long-spanning man-made structures, such as aligned rows of
windows or planar building facades.
