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survey

Multimedia Big Data Analytics: A Survey

Authors:

Samira Pouyanfar,

Shu-Ching Chen,

S. S. IyengarAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 51, Issue 1

Article No.: 10, Pages 1 - 34

https://doi.org/10.1145/3150226

Published: 10 January 2018 Publication History

Abstract

With the proliferation of online services and mobile technologies, the world has stepped into a multimedia big data era. A vast amount of research work has been done in the multimedia area, targeting different aspects of big data analytics, such as the capture, storage, indexing, mining, and retrieval of multimedia big data. However, very few research work provides a complete survey of the whole pine-line of the multimedia big data analytics, including the management and analysis of the large amount of data, the challenges and opportunities, and the promising research directions. To serve this purpose, we present this survey, which conducts a comprehensive overview of the state-of-the-art research work on multimedia big data analytics. It also aims to bridge the gap between multimedia challenges and big data solutions by providing the current big data frameworks, their applications in multimedia analyses, the strengths and limitations of the existing methods, and the potential future directions in multimedia big data analytics. To the best of our knowledge, this is the first survey that targets the most recent multimedia management techniques for very large-scale data and also provides the research studies and technologies advancing the multimedia analyses in this big data era.

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Index Terms

Multimedia Big Data Analytics: A Survey
1. General and reference
  1. Document types
    1. Surveys and overviews
2. Information systems
  1. Information systems applications
    1. Multimedia information systems

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 51, Issue 1

January 2019

743 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3177787

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Sartaj Sahni
Department of Computer and Information Science and Engineering / University of Florida / Gainesville, FL

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Accepted: 01 October 2017

Revised: 01 June 2017

Received: 01 May 2016

Published in CSUR Volume 51, Issue 1

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