We present a system that can match and reconstruct 3D
scenes from extremely large collections of photographs such
as those found by searching for a given city (e.g., Rome) on
Internet photo sharing sites. Our system uses a collection
of novel parallel distributed matching and reconstruction
algorithms, designed to maximize parallelism at each stage
in the pipeline and minimize serialization bottlenecks. It is
designed to scale gracefully with both the size of the problem
and the amount of available computation. We have experimented
with a variety of alternative algorithms at each stage
of the pipeline and report on which ones work best in a
parallel computing environment. Our experimental results
demonstrate that it is now possible to reconstruct cities consisting
of 150K images in less than a day on a cluster with
500 compute cores.
Sameer Agarwal, Noah Snavely, Ian Simon, Steven M.