Fusion in Computer Vision

Understanding Complex Visual Content

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

Buch | Softcover

XIV, 272 Seiten

2016 | Softcover reprint of the original 1st ed. 2014
Springer International Publishing (Verlag)
978-3-319-34774-5 (ISBN)

Artikel merken

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.

A Selective Weighted Late Fusion for Visual Concept Recognition.- Bag-of-Words Image Representation: Key Ideas and Further Insight.- Hierarchical Late Fusion for Concept Detection in Videos.- Fusion of Multiple Visual Cues for Object Recognition in Video.- Evaluating Multimedia Features and Fusion for Example-Based Event Detection.- Rotation-Based Ensemble Classifiers for High Dimensional Data.- Multimodal Fusion in Surveillance Applications.- Multimodal Violence Detection in Hollywood Movies: State-of-the-Art and Benchmarking.- Fusion Techniques in Biomedical Information Retrieval.- Using Crowdsourcing to Capture Complexity in Human Interpretations of Multimedia Content.

Erscheinungsdatum	16.09.2016
Reihe/Serie	Advances in Computer Vision and Pattern Recognition
Zusatzinfo	XIV, 272 p. 74 illus., 65 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Grafik / Design ► Digitale Bildverarbeitung
Schlagworte	Artificial Intelligence • artificial intelligence (incl. robotics) • Bagging and Boosting Methods • Computer Science • computer vision • Contextual Fusion • Data Dimensionality Reduction • Data Mining • data mining and knowledge discovery • Early Fusion • Expert systems / knowledge-based systems • feature fusion • Graphical and digital media applications • Hierarchical and Community-Based Fusion • Image Processing • image processing and computer vision • Kernel Fusion • Late Fusion • Legal, Ethical and Social Concepts of Fusion • Metric Spaces • Multimedia Information Systems • Multimodal fusion • Normalization for Fusion • Robotics • Social Media Fusion and Mining
ISBN-10	3-319-34774-8 / 3319347748
ISBN-13	978-3-319-34774-5 / 9783319347745
Zustand	Neuware