Towards Fast Multimedia Feature Extraction: Hadoop or Storm

Varování

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Autoři	MERA PÉREZ David BATKO Michal ZEZULA Pavel
Rok publikování	2014
Druh	Článek ve sborníku
Konference	Proceedings of 2014 IEEE International Symposium on Multimedia (ISM)
Fakulta / Pracoviště MU	Fakulta informatiky
Citace
Doi	http://dx.doi.org/10.1109/ISM.2014.60
Obor	Informatika
Klíčová slova	Multimedia;Big Data;Feature Extraction;Map Reduce;Apache Storm;Apache Hadoop
Popis	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.
Související projekty:	Centrum pro multi-modální interpretaci dat velkého rozsahu