  Puzzle solving is a difficult problem in its own right, even when the pieces
are all square and build up a natural image. But what if these ideal conditions
do not hold? One such application domain is archaeology, where restoring an
artifact from its fragments is highly important. From the point of view of
computer vision, archaeological puzzle solving is very challenging, due to
three additional difficulties: the fragments are of general shape; they are
abraded, especially at the boundaries (where the strongest cues for matching
should exist); and the domain of valid transformations between the pieces is
continuous. The key contribution of this paper is a fully-automatic and general
algorithm that addresses puzzle solving in this intriguing domain. We show that
our state-of-the-art approach manages to correctly reassemble dozens of broken
artifacts and frescoes.

Computer Vision and Pattern Recognition