Abstract
As the use of digital video is getting popular, there is an increasing demand for efficient retrieval of video. To do that, effective video indexing should be incorporated. One of the most fundamental steps in video indexing is decompose video stream into shots and scenes by parsing. Generally, it takes long time to parse video by traditional sequential computers due to the huge amount of computation. In order to solve this problem and speed up the process, we propose three different parallel scheduling algorithms for heterogeneous distributed multicomputers and compare their performance using extensive simulations. We report some of the results in terms of speedup and load balancing.
This work was supported by grant No. R05-2002-000-01224-0 from the Basic Research Program of the Korea Science & Engineering Foundation.
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© 2003 Springer-Verlag Berlin Heidelberg
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Nam, Y., Hwang, E. (2003). Parallel Parsing of MPEG Video in Heterogeneous Distributed Environment. In: Freire, M.M., Lorenz, P., Lee, M.MO. (eds) High-Speed Networks and Multimedia Communications. HSNMC 2003. Lecture Notes in Computer Science, vol 2720. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45076-4_27
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DOI: https://doi.org/10.1007/978-3-540-45076-4_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40542-9
Online ISBN: 978-3-540-45076-4
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