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A Novel Solution for Scaling Video Shot Boundary Detection Based on Hadoop

Author

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  • Ahmed Dib

    (Badji Mokhtar, Annaba University, Annaba, Algeria)

  • Mokhtar Sellami

    (Badji Mokhtar, Annaba University, Annaba, Algeria)

Abstract

Shot Boundary Detection (SBD) is an important step required by CBVIR systems. In order to perform scalable SBD, a MapReduce based solution is proposed. So, instead of handling consecutive frames in a sequential manner, they can be processed in a fully parallel way. Usually, in the sequential case, descriptors of consecutive frames are compared and shot boundaries are detected if significant variations have occurred. It seems simple, but it can take centuries to processes immense multimedia datasets. Then, based on the transitivity of similarity relation, resemblance measurement between distant frames is calculated, and shout boundaries are extracted respectively by Mapper and Reducer routines. The experiment results show that the proposed solution outperforms the sequential traditional methods and can be applied to a large-scale multimedia datasets.

Suggested Citation

  • Ahmed Dib & Mokhtar Sellami, 2018. "A Novel Solution for Scaling Video Shot Boundary Detection Based on Hadoop," International Journal of Distributed Systems and Technologies (IJDST), IGI Global, vol. 9(3), pages 39-52, July.
    • Handle: RePEc:igg:jdst00:v:9:y:2018:i:3:p:39-52
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