1. A computer implemented method for unsupervised learning of measures for matching objects between images from at least two non-overlapping cameras, comprising: using a processor to perform the steps of: collecting at least two pairs of feature maps, wherein the at least two pairs of feature maps are derived from features of objects captured in the images from the at least two non-overlapping cameras; computing, as a function of the at least two pairs of feature maps, at least first and second match measures, wherein the first match measure is of a same class and the second match measure is of a different class, and wherein objects in the same class are deemed to match; and learning from the at least two pairs of feature maps outlier and inlier distributions, wherein determining the first and second match measures, comprises: computing, as a function of the outlier and inlier distributions, a weight for each of the first and second match measures, and probabilities for the first and second match measures being of the same and different classes.