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Título Fusion in Computer Vision [electronic resource] : Understanding Complex Visual Content / edited by Bogdan Ionescu, Jenny Benois-Pineau, Tomas Piatrik, Georges Quénot.

Descripción física XIV, 272 p. 74 illus., 65 illus. in color. online resource.
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
Colección Advances in Computer Vision and Pattern Recognition, 2191-6586
Advances in Computer Vision and Pattern Recognition, 2191-6586
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Springer eBooks. Computer Science
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Contiene: 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.
Resumen: Visual content understanding is a complex and important challenge for applications in automatic multimedia information indexing, medicine, robotics, and surveillance. Yet the performance of such systems can be improved by the fusion of individual modalities/techniques for content representation and machine learning. This comprehensive text/reference presents a thorough overview of Fusion in Computer Vision, from an interdisciplinary and multi-application viewpoint. Presenting contributions from an international selection of experts, the work describes numerous successful approaches, evaluated in the context of international benchmarks that model realistic use cases at significant scales. Topics and features: Examines late fusion approaches for concept recognition in images and videos, including the bag-of-words model 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 This authoritative collection is essential reading for researchers and students interested in the domain of information fusion for complex visual content understanding, and related fields.
Materia Computer science.
Data mining.
Multimedia information systems.
Artificial intelligence.
Image processing.
Computer Science.
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Image Processing and Computer Vision.
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Multimedia Information Systems.
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Artificial Intelligence (incl. Robotics).
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Data Mining and Knowledge Discovery.
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Autor secundario Ionescu, Bogdan., editor.
Benois-Pineau, Jenny., editor.
Piatrik, Tomas., editor.
Quénot, Georges., editor.
SpringerLink (Online service)
En Springer eBooks
OTRO SOPORTE Printed edition: 9783319056951
ISBN 9783319056968 978-3-319-05696-8
ISBN/ISSN 10.1007/978-3-319-05696-8 doi