Overview
- Examines information fusion in the context of multimodal and multidimensional data representation, i.e., video, image and text
- Presents a focus on information fusion for tackling higher-level description of multimedia information
- Discusses the latest research on a broad range of multimedia information fusion techniques
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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About this book
This book presents a thorough overview of fusion in computer vision, from an interdisciplinary and multi-application viewpoint, describing successful approaches, evaluated in the context of international benchmarks that model realistic use cases. Features: examines late fusion approaches for concept recognition in images and videos; describes the interpretation of visual content by incorporating models of the human visual system with content understanding methods; investigates the fusion of multi-modal features of different semantic levels, as well as results of semantic concept detections, for example-based event recognition in video; proposes rotation-based ensemble classifiers for high-dimensional data, which encourage both individual accuracy and diversity within the ensemble; reviews application-focused strategies of fusion in video surveillance, biomedical information retrieval, and content detection in movies; discusses the modeling of mechanisms of human interpretation of complex visual content.
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Editors and Affiliations
About the editors
Dr. Bogdan Ionescu is a lecturer and Coordinator of the Video Processing Group at the Image Processing and Analysis Laboratory, University Politehnica of Bucharest, Romania. Dr. Jenny Benois-Pineau is a full professor and Chair of the Video Analysis and Indexing research group at the University of Bordeaux, France. Dr. Tomas Piatrik is a senior researcher in the Multimedia and Vision Research Group at Queen Mary University of London, UK. Dr. Georges Quénot is a senior researcher at CNRS and leader of the Multimedia Information Modeling and Retrieval group at the Grenoble Informatics Laboratory, France.
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Bibliographic Information
Book Title: Fusion in Computer Vision
Book Subtitle: Understanding Complex Visual Content
Editors: Bogdan Ionescu, Jenny Benois-Pineau, Tomas Piatrik, Georges Quénot
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-3-319-05696-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-05695-1Published: 10 April 2014
Softcover ISBN: 978-3-319-34774-5Published: 03 September 2016
eBook ISBN: 978-3-319-05696-8Published: 25 March 2014
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: XIV, 272
Number of Illustrations: 9 b/w illustrations, 65 illustrations in colour
Topics: Image Processing and Computer Vision, Multimedia Information Systems, Artificial Intelligence, Data Mining and Knowledge Discovery
Keywords
- Bagging and Boosting Methods
- Contextual Fusion
- Data Dimensionality Reduction
- Early Fusion
- Feature Fusion
- Hierarchical and Community-Based Fusion
- Kernel Fusion
- Late Fusion
- Legal, Ethical and Social Concepts of Fusion
- Metric Spaces
- Multimodal Fusion
- Normalization for Fusion
- Social Media Fusion and Mining