Distributed Video Decoding on Hadoop-Reference-Cited by-同舟云学术

Distributed Video Decoding on Hadoop

Published:2018-12-01 Issue:12 Volume:E101.D Page:2933-2941
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

YOON Illo¹,YI Saehanseul¹,OH Chanyoung¹,JUNG Hyeonjin¹,YI Youngmin¹

Affiliation:

1. School of Electrical and Computer Engineering, University of Seoul

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E101.D/12/E101.D_2018PAP0014/_pdf

Reference15 articles.

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2. [2] M. Kim, Y. Cui, S. Han, and H. Lee, “Towards efficient design and implementation of a hadoop-based distributed video transcoding system in cloud computing environment,” International Journal of Multimedia and Ubiquitous Engineering, vol.8, no.2, pp.213-224, 2013.

3. [3] Xuggler, “Xuggler api,” Avaliable: http://www.xuggle.com/xuggler/ [Accessed: 25 April 2015], 2012.

4. [4] H. Tan and L. Chen, “An approach for fast and parallel video processing on Apache Hadoop clusters,” Multimedia and Expo (ICME), 2014 IEEE International Conference on, pp.1-6, IEEE, 2014. 10.1109/icme.2014.6890135

5. [5] “Javacv project page on google code,” Avaliable: http://code.google.com/p/javacv [Accessed: 20 Aug. 2012].

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