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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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Detaylı Bibliyografya
Müşterek Yazar: SpringerLink (Online service)
Diğer Yazarlar: Turaga, Pavan K. (Editör), Srivastava, Anuj (Editör)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edisyon:1st ed. 2016.
Konular:
Online Erişim:Full-text access
OPAC'ta görüntüle
Diğer Bilgiler
Özet: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).   ·         Illustrates Riemannian computing theory on applications in computer vision, machine learning, and robotics ·         Emphasis on algorithmic advances that will allow re-application in other contexts ·         Written by leading researchers in computer vision and Riemannian computing, from universities and industry.
Fiziksel Özellikler:VI, 391 p. 88 illus., 66 illus. in color. online resource.
ISBN:9783319229577
DOI:10.1007/978-3-319-22957-7