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Riemannian Computing in Computer Vision

Riemannian Computing in Computer Vision by Pavan K. Turaga
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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).
Springer International Publishing; November 2015
382 pages; ISBN 9783319229577
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Title: Riemannian Computing in Computer Vision
Author: Pavan K. Turaga; Anuj Srivastava
 
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