Computational Geometry With Independent And Dependent Uncertainties

Rivka Gitik, Leo Joskowicz

ISBN 10: 9811253838 / ISBN 13: 9789811253836

Published by World Scientific Publishing Co Pte Ltd, SG, 2022

About this Item

This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.

Seller Inventory # LU-9789811253836

Bibliographic Details

• Title: Computational Geometry With Independent And Dependent Uncertainties
• Publisher: World Scientific Publishing Co Pte Ltd, SG
• Publication Date: 2022
• Language: English
• ISBN 10: 9811253838
• ISBN 13: 9789811253836
• Binding: Hardback
• Condition: New

About this title

Synopsis

This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry. The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies. This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.