Riemannian Computing in Computer Vision (Hardcover, 1st ed. 2016)

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).

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	November 2015
First published:	2016
Editors:	Pavan K Turaga • Anuj Srivastava
Dimensions:	235 x 155 x 22mm (L x W x T)
Format:	Hardcover
Pages:	391
Edition:	1st ed. 2016
ISBN-13:	978-3-319-22956-0
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > General Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	3-319-22956-7
Barcode:	9783319229560

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