Fusion in Computer Vision
Understanding Complex Visual Content
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.
| ISBN: | 9783319347745 |
|---|---|
| Sprache: | Englisch |
| Seitenzahl: | 272 |
| Produktart: | Kartoniert / Broschiert |
| Herausgeber: | Benois-Pineau, Jenny Ionescu, Bogdan Piatrik, Tomas Quénot, Georges |
| Verlag: | Springer International Publishing |
| Veröffentlicht: | 03.09.2016 |
| Untertitel: | Understanding Complex Visual Content |
| 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 |
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