Fusion in Computer Vision
Understanding Complex Visual Content
Editors: Ionescu, B., Benois-Pineau, J., Piatrik, T., Quénot, G. (Eds.)
Free Preview- 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
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- About this book
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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.
- About the authors
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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.
- Table of contents (10 chapters)
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A Selective Weighted Late Fusion for Visual Concept Recognition
Pages 1-28
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Bag-of-Words Image Representation: Key Ideas and Further Insight
Pages 29-52
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Hierarchical Late Fusion for Concept Detection in Videos
Pages 53-77
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Fusion of Multiple Visual Cues for Object Recognition in Videos
Pages 79-107
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Evaluating Multimedia Features and Fusion for Example-Based Event Detection
Pages 109-133
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Table of contents (10 chapters)
- Download Preface 1 PDF (65.2 KB)
- Download Sample pages 2 PDF (1.5 MB)
- Download Table of contents PDF (63.3 KB)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Fusion in Computer Vision
- Book Subtitle
- Understanding Complex Visual Content
- Editors
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- Bogdan Ionescu
- Jenny Benois-Pineau
- Tomas Piatrik
- Georges Quénot
- Series Title
- Advances in Computer Vision and Pattern Recognition
- Copyright
- 2014
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-05696-8
- DOI
- 10.1007/978-3-319-05696-8
- Hardcover ISBN
- 978-3-319-05695-1
- Softcover ISBN
- 978-3-319-34774-5
- Series ISSN
- 2191-6586
- Edition Number
- 1
- Number of Pages
- XIV, 272
- Number of Illustrations
- 9 b/w illustrations, 65 illustrations in colour
- Topics
