Riemannian Computing and Statistical Inferences in Computer Vision
ISBN 10: 3319229567 ISBN 13: 9783319229560
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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).
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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Title: Riemannian Computing and Statistical ...
Publisher: Springer
Publication Date: 2015
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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
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Buch. Condition: Neu. Riemannian Computing in Computer Vision | Anuj Srivastava (u. a.) | Buch | vi | Englisch | 2015 | Springer International Publishing | EAN 9783319229560 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 104453855
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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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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volumeincludes 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).Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 400 pp. Englisch. Seller Inventory # 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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