A kernel-based framework for image collection exploration
Journal of Visual Languages and Computing
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In this paper we address two relevant tasks in image visualisation research: layout methods for presenting content and relations within image databases; and optimal solutions for efficient use of the entire display space. We introduce a novel approach to enable users searching on large image archives to distinguish heterogeneous sets of images. Thus, helping them to navigate or browse image databases according to relevant query directions. Two methods for mapping similarity relations between images and cognitive partitioning of the display space are presented.