An attention based similarity measure used to identify image clusters

This paper outlines a new attention based similarity measure and describes an application to the problem of identifying image clusters in a 4 class problem. A diverse set of images was obtained using camera phones in 4 separate locations and classification performance was tested against the true location of the images. The approach promises to have application to the unsupervised extraction of unknown numbers of clusters in larger datasets.