Riemannian computing in computer vision
This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approa...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Cham, Heidelberg, New York, Dordrecht, London
Springer
2016
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| Online Zugang: | Inhaltstext |
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Tag hinzufügen | Zusammenfassung: | This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approaches in problems such as face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion. Some of the mathematical entities that necessitate a geometric analysis include rotation matrices (e.g. in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours). |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | vi, 391 Seiten Illustrationen, Diagramme |
| ISBN: | 3319229567 3-319-22956-7 9783319229560 978-3-319-22956-0 |