Semantic video fingerprinting and retrieval using face information
Image Communication
Frontiers of Computer Science: Selected Publications from Chinese Universities
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We present a multiresolution approach for video indexing and feature matching of subband-coded video databases. Four different scene-change detectors were tested; scene-change detection is applied only on the lowest subband for computational efficiency. Two kinds of scene changes, abrupt and smoothly accumulated, mark the beginning of new scene segments. The index for each scene segment is the pair of the histograms of two representative frames, the first and the last frame of the scene. Using the approach of query by example, the index-matching algorithm takes a multiresolution 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 the finest resolution is reached. Experimental results are presented, and the proposed indexing technique appears to be promising for its speed and its inherent hierarchical search procedure