S.H. Kim and R.-H. Park (Korea)
luminance projection, video sequencematching, key frame extraction, video indexing,Hausdorff distance
An effective video indexing is required to manipulate large video databases. Most algorithms for video indexing have been commonly used histograms, edges, or motion features. In this paper, we propose an efficient algorithm using the luminance projection for video indexing. To effectively index the video sequences and to reduce the computational complexity, we use the key frames extracted by the cumulative measure, and compare the set of key frames using the modified Hausdorff distance. Experimental results show that the proposed video indexing and sequence matching algorithm yields the higher accuracy and performance than the conventional algorithm.
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