  Several methods have been proposed for large-scale 3D reconstruction from
large, unorganized image collections. A large reconstruction problem is
typically divided into multiple components which are reconstructed
independently using structure from motion (SFM) and later merged together.
Incremental SFM methods are most popular for the basic structure recovery of a
single component. They are robust and effective but are strictly sequential in
nature. We present a multistage approach for SFM reconstruction of a single
component that breaks the sequential nature of the incremental SFM methods. Our
approach begins with quickly building a coarse 3D model using only a fraction
of features from given images. The coarse model is then enriched by localizing
remaining images and matching and triangulating remaining features in
subsequent stages. These stages are made efficient and highly parallel by
leveraging the geometry of the coarse model. Our method produces similar
quality models as compared to incremental SFM methods while being notably fast
and parallel.
