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A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability

The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections.

Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data.

Addresses the area of multimedia retrieval and pays close attention to the issue of scalability
Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios
Includes tables, illustrations, and figures
Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools
Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.



TABLE OF CONTENTS
About the companion website

Chapter 1: Introduction

Chapter 2: Feature extraction from big multimedia data

2.1. Representation Learning, Models and Practice

2.2. Concept-based and event-based search in large video collections

2.3. Big Data Multimedia Mining: Feature Extraction facing Volume, Velocity, and Variety

Chapter 3: Learning algorithms for large scale multimedia

3.1. Large Scale Video Understanding with Limited Training Labels

3.2. Multimodal fusion of big multimedia data

3.3. Large-Scale Social Multimedia Analysis

3.4. Privacy and audiovisual content: Protecting users as big multimedia data grows bigger

Chapter 4: Scalability in multimedia access

4.1. Data Storage and Management for Big Multimedia

4.2. Perceptual hashing for large-scale multimedia search

Chapter 5: Applications of large scale multimedia search

5.1. Image tagging with deep learning: Fine-grained Visual Analysis

5.2. Visually Exploring Millions of Images Using Image Maps and Graphs

5.3. Medical Decision Support Using Increasingly Large Multimodal Data Sets

Chapter 6: Conclusions and future trends