Realtime semantic enrichment of video streams in the age of big data

被引:0
|
作者
Montagnuolo M. [1 ]
Platter P. [2 ]
Bosca A. [3 ]
Bidotti N. [4 ]
Messina A. [5 ]
机构
[1] Research and Development Department, Italian Public Broadcaster RAI, Torino
[2] AgileLab, Torino
[3] Polytechnic University, Turin
[4] Università degli Studi di Torino, Turin
来源
SMPTE Motion Imaging Journal | 2019年 / 128卷 / 01期
关键词
Big data applications; Content-based retrieval; Distributed information systems; Pipeline processing; Semantic web;
D O I
10.5594/JMI.2018.2880364
中图分类号
学科分类号
摘要
This paper describes AgileRAI, a framework for searching, organizing, and accessing multimedia data in a fast and semantic-driven way. AgileRAI supports realtime ingestion of video streams on which different machine-learning techniques (such as global and local visual features extraction and matching) are applied in a parallel and scalable way. Extracted features are matched to a reference database of visual patterns (e.g., faces, logos, and monuments) in order to produce a set of metatags describing the ingested contents. Furthermore, these tags are semantically enriched using open semantic data repositories. The system is designed with a scaleout pattern architecture based on Apache Spark, ensuring high performance in Big Data management environments. © 2019 SMPTE.
引用
收藏
页码:1 / 8
页数:7
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