Uncertain projective geometry :statistical reasoning for polyhedral object reconstruction
- 作者: Heuel, Stephan.
- 出版: Berlin ;New York : Springer ©2004.
- 稽核項: 1 online resource (xvi, 205 pages) :illustrations.
- 叢書名: Lecture notes in computer science,3008 , Tutorial
- 標題: Bildrekonstruktion , Mehrdimensionale Bildverarbeitung , MATHEMATICS , Geometry, Projective , image processing. , Traitement d'images. , GeometryGeneral. , Méthodes statistiques. , Géométrie algébrique. , Projektive Geometrie , Géométrie projective. , Géométrie projective , Statistical methods. , MATHEMATICS Geometry -- General. , Geometry, Projective Statistical methods. , Geometry, Projective. , Electronic books. , Statistisches Modell , Geometrisches Objekt , Image processing. , Géométrie projective Méthodes statistiques. , Unsicherheit
- ISBN: 1280307625 , 9781280307621
- ISBN: 9783540220299 , 3540220291 , 0302-9743 ;
- 試查全文@TNUA:
- 附註: Includes bibliographical references (pages 197-205). 1 Introduction -- 2 Representation of Geometric Entities and Transformations -- 3 Geometric Reasoning Using Projective Geometry -- 4 Statistical Geometric Reasoning -- 5 Polyhedral Object Reconstruction -- 6 Conclusions -- A Notation -- B Linear Algebra -- C Statistics.
- 摘要: 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.
- 電子資源: https://dbs.tnua.edu.tw/login?url=https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=133866
- 系統號: 005317814
- 資料類型: 電子書
- 讀者標籤: 需登入
- 引用網址: 複製連結
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.
來源: Google Book
來源: Google Book
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