A Novel Solution for Scaling Video Shot Boundary Detection Based on Hadoop
Ahmed Dib and
Mokhtar Sellami
Additional contact information
Ahmed Dib: Badji Mokhtar, Annaba University, Annaba, Algeria
Mokhtar Sellami: Badji Mokhtar, Annaba University, Annaba, Algeria
International Journal of Distributed Systems and Technologies (IJDST), 2018, vol. 9, issue 3, 39-52
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.
Date: 2018
References: Add references at CitEc
Citations:
Downloads: (external link)
https://services.igi-global.com/resolvedoi/resolve ... 018/IJDST.2018070103 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:igg:jdst00:v:9:y:2018:i:3:p:39-52
Access Statistics for this article
International Journal of Distributed Systems and Technologies (IJDST) is currently edited by Nik Bessis
More articles in International Journal of Distributed Systems and Technologies (IJDST) from IGI Global
Bibliographic data for series maintained by Journal Editor ().