We develop linear sketches for estimating the Earth-Mover distance between two point sets, i.e., the cost of the minimum weight matching between the points according to some metric. While Euclidean distance and Edit distance are natural measures for vectors and strings respectively, Earth-Mover distance is a well-studied measure that is natural in the context of visual or metric data. Our work considers the case where the points are located at the nodes of an implicit graph and define the distance between two points as the length of the shortest path between these points. We first improve and simplify an existing result by Brody et al. [4] for the case where the graph is a cycle. We then generalize our results to arbitrary graph metrics. Our approach is to recast the problem of estimating Earth-Mover distance in terms of an l_1 regression problem. The resulting linear sketches also yield space-efficient data stream algorithms in the usual way.
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