Towards Fast Multimedia Feature Extraction: Hadoop or Storm

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Authors

MERA PÉREZ David BATKO Michal ZEZULA Pavel

Year of publication 2014
Type Article in Proceedings
Conference Proceedings of 2014 IEEE International Symposium on Multimedia (ISM)
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1109/ISM.2014.60
Field Informatics
Keywords Multimedia;Big Data;Feature Extraction;Map Reduce;Apache Storm;Apache Hadoop
Description 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.
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