Fusion in Computer Vision : Understanding Complex Visual Content
Language: English
Published by Springer, 2014
Series: Book 39 of 86 - Advances in Computer Vision and Pattern Recognition
- Hardcover
- Used

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Zustand: Sehr gut | Seiten: 288 | Sprache: Englisch | Produktart: Bücher | 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.
Seller Inventory # 24571351/12
- Title
- Fusion in Computer Vision : Understanding Complex Visual Content
- Author
- Unbekannt
- Publisher
- Springer
- Publication year
- 2014
- Condition
- Sehr gut
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319056956
- ISBN 13
- 9783319056951
- Series
- Book 39 of 86: Advances in Computer Vision and Pattern Recognition
- Seller catalogs
- Bücher
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.
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
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