 Computing the Earth Mover's Distance under Transformations
This project aims at extending the Earth Mover's Distance (EMD) between
distributions to be invariant to some given set of distribution
transformations. This problem is motivated by examples from contentbased
image retrieval. A monotonically convergent iteration is given, although
the iteration may converge to only a locally optimal transformation.
Specific cases are identified in which a globally optimal transformation
can be computed directly, without the aid of our iteration.
A gentle introduction to the EMD is also included.
