In this paper we present a multiresolution approach for video indexing and feature matching of subband coded video databases. Subband coding refers to a coding technique where the input images are quantized after being decomposed into several narrow spatial frequency bands by filtering and decimation. Five different approaches were tested for scene change detection which is applied only on the lowest subband for computational efficiency. Two kinds of scene changes, abrupt and smoothly accumulated scene changes, mark the beginning of new scene segments. An index for each scene segment is the histogram of two representative frames, which we take to be the first and the last frame of the scene for simplicity. Using the approach of query by example, the index matching algorithm takes a multi-resolution approach by hierarchically comparing histograms at different resolutions. The search algorithm for the match between example query and its target scene segment starts from the coarsest resolution, and moves to the next finer resolution until a single match is obtained or the finest resolution is reached. Experimental results are presented, and the proposed indexing technique appears to be promising for its computational efficiency and its inherent hierarchical search procedure.
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