Structure Driven Image Database Retrieval

Part of Advances in Neural Information Processing Systems 10 (NIPS 1997)

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Jeremy De Bonet, Paul Viola


A new algorithm is presented which approximates the perceived visual similarity between images. The images are initially trans(cid:173) formed into a feature space which captures visual structure, tex(cid:173) ture and color using a tree of filters. Similarity is the inverse of the distance in this perceptual feature space. Using this algorithm we have constructed an image database system which can perform example based retrieval on large image databases. Using carefully constructed target sets, which limit variation to only a single visual characteristic, retrieval rates are quantitatively compared to those of standard methods.