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Riemannian Computing in Computer Vision

Riemannian Computing in Computer Vision This link for educational purpose only. Please remove file from your computer after familiarization.

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).

Book year:

Book pages: 382

ISBN: 3319229567

Book language: en

File size: 10.47 MB

File type: pdf

Published: 04 May 2019 - 22:06