Fusion in Computer Vision (eBook)

Understanding Complex Visual Content

Bogdan Ionescu, Jenny Benois-Pineau, Tomas Piatrik, Georges Quénot (Herausgeber)

eBook Download: PDF

2014 | 2014
XIV, 272 Seiten
Springer International Publishing (Verlag)
978-3-319-05696-8 (ISBN)

Infos

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.

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.

Inhalt

A Selective Weighted Late Fusion for Visual Concept RecognitionNingning Liu, Emmanuel Dellandréa, Bruno Tellez, and Liming ChenBag-of-Words Image Representation: Key Ideas and Further InsightMarc T. Law, Nicolas Thome, and Matthieu CordHierarchical Late Fusion for Concept Detection in VideosSabin Tiberius Strat, Alexandre Benoit, Patrick Lambert, Hervé Bredin, and Georges QuénotFusion of Multiple Visual Cues for Object Recognition in VideoI. Gonsalez-Diaz, J. Benois-Pineau, V. Buso, and H. BoujutEvaluating Multimedia Features and Fusion for Example-Based Event DetectionGregory K. Myers, Cees G.M. Snoek, Ramakant Nevatia, Ramesh Nallapati, Julien van Hout, Stephanie Pancoast, Chen Sun, Amirhossein Habibian, Dennis C. Koelma, Koen E. A. van de Sande, and Arnold W.M. SmeuldersRotation-Based Ensemble Classifiers for High Dimensional DataJunshi Xia, Jocelyn Chanussot, Peijun Du, and Xiyan HeMultimodal Fusion in Surveillance ApplicationsVirginia Fernandez Arguedas, Qianni Zhang, and Ebroul IzquierdoMultimodal Violence Detection in Hollywood Movies: State-of-the-Art and BenchmarkingClaire-Hélene Demarty and Cédric Penet and Bogdan Ionescu and Guillaume Gravier, and Mohammad SoleymaniFusion Techniques in Biomedical Information RetrievalAlba Garcıa Seco de Herrera and Henning MullerUsing Crowdsourcing to Capture Complexity in Human Interpretations of Multimedia ContentMartha Larson, Mark Melenhorst, Maria Menendez, and Peng Xu

Produkt-Details

• Erscheint lt. Verlag: 25.3.2014
• Reihe/Serie: Advances in Computer Vision and Pattern Recognition
• Reihe/Serie: Advances in Computer Vision and Pattern Recognition
• Zusatzinfo: XIV, 272 p. 74 illus., 65 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Mathematik / Informatik ► Informatik ► Grafik / Design
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Schlagworte: 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
• ISBN-10: 3-319-05696-4 / 3319056964
• ISBN-13: 978-3-319-05696-8 / 9783319056968