[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5392/IJoC.2010.6.3.005

Content similarity matching for video sequence identification

Kim, Sang-Hyun (School of Electrical Engineering, College of Science and Engineering Kyungpook National University)

Publication Information

International Journal of Contents / v.6, no.3, 2010 , pp. 5-9 More about this Journal

Abstract

To manage large database system with video, effective video indexing and retrieval are required. A large number of video retrieval algorithms have been presented for frame-wise user query or video content query, whereas a few video identification algorithms have been proposed for video sequence query. In this paper, we propose an effective video identification algorithm for video sequence query that employs the Cauchy function of histograms between successive frames and the modified Hausdorff distance. To effectively match the video sequences with a low computational load, we make use of the key frames extracted by the cumulative Cauchy function and compare the set of key frames using the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed algorithm for video identification yields remarkably higher performance than conventional algorithms such as Euclidean metric, and directed divergence methods.

Keywords

Content Similarity; Video Identification; Modified Hausdorff Distance; and Cauchy Function;

Citations & Related Records

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