ENGLISH

Uncertain Projective Geometry: Statistical Reasoning for Polyhedral Object Reconstruction

By Stephan Heuel (auth.)

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
2004
ISBN
3540246568, 3540220291, 9783540220299
DOI
10.1007/b97201
LCC
QA471 .H573 2004
Open Library ID
OL3314346M
Language
english
Format
PDF
Filesize
7 MB (7812357 bytes)
Series
Lecture Notes in Computer Science 3008
Edition
1
Pages
210\226
Library
kolxoz
Time added
2010-02-18 13:16:04
Pattern Recognition; Image Processing and Computer

Description

Algebraic projective geometry, with its multilinear relations and its embedding into Grassmann-Cayley algebra, has become the basic representation of multiple view geometry, resulting in deep insights into the algebraic structure of geometric relations, as well as in efficient and versatile algorithms for computer vision and image analysis. This book provides a coherent integration of algebraic projective geometry and spatial reasoning under uncertainty with applications in computer vision. Beyond systematically introducing the theoretical foundations from geometry and statistics and clear rules for performing geometric reasoning under uncertainty, the author provides a collection of detailed algorithms. The book addresses researchers and advanced students interested in algebraic projective geometry for image analysis, in statistical representation of objects and transformations, or in generic tools for testing and estimating within the context of geometric multiple-view analysis.

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