This paper presents an overview of our recent work on managing image and video data. The first half of the paper describes a representation for the semantic spatial layout of video frames. In particular, Markov random fields are used to characterize the spatial arrangement of frame tiles that are labeled using support vector machine classifiers. The representation is shown to support similarity retrieval at the semantic level as demonstrated in a prototype video management system. The second

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... f of the paper describes a method for efficiently computing nearest neighbor queries in high-dimensional feature spaces in a relevance feedback framework.