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@inproceedings{1225538,
author = {Mera Pérez, David and Batko, Michal and Zezula, Pavel},
address = {Washington, DC},
booktitle = {Proceedings of 2014 IEEE International Symposium on Multimedia (ISM)},
doi = {http://dx.doi.org/10.1109/ISM.2014.60},
editor = {Qiong Liu, Mei-Ling Shyu, James Joshi},
keywords = {Multimedia;Big Data;Feature Extraction;Map Reduce;Apache Storm;Apache Hadoop},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Washington, DC},
isbn = {978-1-4799-4311-1},
pages = {106-109},
publisher = {IEEE Computer Society Publications},
title = {Towards Fast Multimedia Feature Extraction: Hadoop or Storm},
year = {2014}
}
TY - JOUR
ID - 1225538
AU - Mera Pérez, David - Batko, Michal - Zezula, Pavel
PY - 2014
TI - Towards Fast Multimedia Feature Extraction: Hadoop or Storm
PB - IEEE Computer Society Publications
CY - Washington, DC
SN - 9781479943111
KW - Multimedia;Big Data;Feature Extraction;Map Reduce;Apache Storm;Apache Hadoop
N2 - The current explosion of data accelerated evolution of various content-based indexing techniques that allow to efficiently search in multimedia data such as images. However, indexable features must be first extracted from the raw images before the indexing. This necessary step can be very time consuming for large datasets thus parallelization is desirable to speed the process up. In this paper, we experimentally compare two approaches to distribute the task among multiple machines: the Apache Hadoop and the Apache Storm projects.
ER -
MERA PÉREZ, David, Michal BATKO and Pavel ZEZULA. Towards Fast Multimedia Feature Extraction: Hadoop or Storm. In Qiong Liu, Mei-Ling Shyu, James Joshi. \textit{Proceedings of 2014 IEEE International Symposium on Multimedia (ISM)}. Washington, DC: IEEE Computer Society Publications, 2014, p.~106-109. ISBN~978-1-4799-4311-1. Available from: https://dx.doi.org/10.1109/ISM.2014.60.
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