Fusion in Computer Vision: Understanding Complex Visual Content: Advances in Computer Vision and Pattern Recognition
Editat de Bogdan Ionescu, Jenny Benois-Pineau, Tomas Piatrik, Georges Quénoten Limba Engleză Hardback – 10 apr 2014
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Springer International Publishing – 10 apr 2014 | 335.90 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783319056951
ISBN-10: 3319056956
Pagini: 272
Ilustrații: XIV, 272 p. 74 illus., 65 illus. in color.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.7 kg
Ediția:2014
Editura: Springer International Publishing
Colecția Springer
Seria Advances in Computer Vision and Pattern Recognition
Locul publicării:Cham, Switzerland
ISBN-10: 3319056956
Pagini: 272
Ilustrații: XIV, 272 p. 74 illus., 65 illus. in color.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.7 kg
Ediția:2014
Editura: Springer International Publishing
Colecția Springer
Seria Advances in Computer Vision and Pattern Recognition
Locul publicării:Cham, Switzerland
Public țintă
ResearchCuprins
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.
Notă biografică
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.
Textul de pe ultima copertă
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:
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 diversitywithin 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
Caracteristici
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 Includes supplementary material: sn.pub/extras