1. A computer-implemented method comprising: determining a set of one or more feature values for each digital image in a collection of digital images, wherein the set of feature values includes an edge compactness feature value that is an indication of the number of objects in the digital image that are useful for scene matching, wherein the indicated number of objects excludes at least a portion of the digital image; determining a subset of the collection of digital images that are good candidates for scene matching by applying a classifier responsive to the determined feature values; applying a scene matching algorithm to the subset of the collection of digital images to identify groups of digital images having matching backgrounds; and storing an indication of the identified groups of digital images having matching backgrounds in a processor-accessible memory, wherein the step of determining the edge compactness feature value includes: detecting any persons present in the digital image; determining a non-person region in the digital image that excludes any detected persons; determining an edge map for the determined non-person region of the digital image; grouping edges within the edge map into spatially compact clusters; and computing the edge compactness feature value responsive to based on the number of spatially compact clusters into which the edges are grouped.