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Springer - Riemannian Computing in Computer Vision Book

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Description

Riemannian Computing in Computer Vision by Springer provides a deep look into Riemannian geometric computations and statistical inferences applied to computer vision. This edited volume brings together contributions from leading experts who use geometric approaches to solve complex problems in the field. Readers will explore how these mathematical methods apply to practical tasks such as face recognition, activity recognition, and object detection. The book also covers specialized areas like biomedical image analysis and structure-from-motion. By examining mathematical entities like rotation matrices used in modeling camera motion, this text offers a technical foundation for understanding geometric analysis in modern vision systems.

Key Features

Covers Riemannian geometric computations and statistical inferences for various computer vision applications.

Includes expert contributions on face recognition, activity recognition, and object detection techniques.

Provides technical analysis for biomedical image analysis and structure-from-motion problems.

Explains the use of rotation matrices for modeling camera motion through geometric analysis.

Offers a comprehensive treatise on applying geometric approaches to complex vision tasks.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
18 November 2015
Listed Since
09 July 2015

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