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http://dx.doi.org/10.5762/KAIS.2015.16.12.8649

Efficient Video Retrieval Scheme with Luminance Projection Model  

Kim, Sang Hyun (School of Convergence & Fusion System Engineering, Kyungpook National University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.16, no.12, 2015 , pp. 8649-8653 More about this Journal
Abstract
A number of video indexing and retrieval algorithms have been proposed to manage large video databases efficiently. The video similarity measure is one of most important technical factor for video content management system. In this paper, we propose the luminance characteristics model to measure the video similarity efficiently. Most algorithms for video indexing have been commonly used histograms, edges, or motion features, whereas in this paper, the proposed algorithm is employed an efficient similarity measure using the luminance projection. To index the video sequences effectively and to reduce the computational complexity, we calculate video similarity using 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 luminance projection model yields the remarkable improved accuracy and performance than the conventional algorithm such as the histogram comparison method, with the low computational complexity.
Keywords
luminance projection; video similarity measure; video indexing; key frame extraction; modified Hausdorff distance; video retrieval;
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