Two novel problems straddling the boundary between image retrieval and data mining are formulated: for every pixel in the query image, (i) find the database image with the maximum resolution depicting the pixel and (ii) find the frequency with which it is photographed in detail. An efficient and reliable solution for both problems is proposed based on two novel techniques, the hierarchical query expansion that exploits the document at a time (DAAT) inverted file and a geometric consistency verification sufficiently robust to prevent topic drift within a zooming search. Experiments show that the proposed method finds surprisingly fine details on landmarks, even those that are hardly noticeable for humans.
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