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Synopsis
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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About the Author
Pavan Turaga is an Assistant Professor at Arizona State University Anuj Srivastava is a Professor at Florida State University
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- PublisherSpringer
- Publication date2015
- ISBN 10 3319229567
- ISBN 13 9783319229560
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages397
- EditorTuraga Pavan K., Srivastava Anuj
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Riemannian Computing in Computer Vision.
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vi, 391 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Seller Inventory # 4739FB
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Riemannian Computing and Statistical Inferences in Computer Vision
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Riemannian Computing and Statistical Inferences in Computer Vision
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Riemannian Computing and Statistical Inferences in Computer Vision
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Riemannian Computing in Computer Vision
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Riemannian Computing in Computer Vision
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ISBN 10: 3319229567
ISBN 13: 9783319229560
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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). 400 pp. Englisch. Seller Inventory # 9783319229560
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Riemannian Computing in Computer Vision
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Riemannian Computing in Computer Vision
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ISBN 10: 3319229567
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Illustrates Riemannian computing theory on applications in computer vision, machine learning, and roboticsEmphasis on algorithmic advances that will allow re-application in other contextsWritten by leading researchers in computer vision and. Seller Inventory # 39553401
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Riemannian Computing in Computer Vision
Published by
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ISBN 10: 3319229567
ISBN 13: 9783319229560
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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). Seller Inventory # 9783319229560
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Riemannian Computing in Computer Vision
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