E-Book, Englisch, 272 Seiten, eBook
Ionescu / Benois-Pineau / Piatrik Fusion in Computer Vision
2014
ISBN: 978-3-319-05696-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Understanding Complex Visual Content
E-Book, Englisch, 272 Seiten, eBook
Reihe: Advances in Computer Vision and Pattern Recognition
ISBN: 978-3-319-05696-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
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 Garcia Seco de Herrera and Henning MullerUsing Crowdsourcing to Capture Complexity in Human Interpretations of Multimedia ContentMartha Larson, Mark Melenhorst, Maria Menendez, and Peng Xu




