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Invitation to 3-D Vision, An.

Author: Shankar Sastry; Yi Ma; Stefano Soatto; Jana Kosecka
Publisher: New York, NY : Springer, 2003.
Series: Interdisciplinary applied mathematics.
Edition/Format:   eBook : Document : English
Summary:
This book gives senior undergraduate and beginning graduate students and researchers in computer vision, applied mathematics, computer graphics, and robotics a self-contained introduction to the geometry of 3D vision; that is the reconstruction of 3D models of objects from a collection of 2D images. Following a brief introduction, Part I provides background materials for the rest of the book. The two fundamental  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Sastry, Shankar.
Invitation to 3-D Vision, An: From Images to Geometric Models.
New York, NY : Springer, ©2003
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Shankar Sastry; Yi Ma; Stefano Soatto; Jana Kosecka
ISBN: 9780387008936 0387008934
OCLC Number: 1027160488
Notes: ""9.1 Incidence relations among points, lines, and planes""
Description: 1 online resource (542 pages).
Contents: ""Table of Contents""; ""Preface""; ""Acknowledgments""; ""Chapter 1 Introduction""; ""1.1 Visual perception from 2-D images to 3-D models""; ""1.2 A mathematical approach""; ""1.3 A historical perspective""; ""Part I Introductory Material""; ""Chapter 2 Representation of a Three-Dimensional Moving Scene""; ""2.1 Three-dimensional Euclidean space""; ""2.2 Rigid-body motion""; ""2.3 Rotational motion and its representations""; ""2.4 Rigid-body motion and its representations""; ""2.5 Coordinate and velocity transformations""; ""2.6 Summary""; ""2.7 Exercises"" ""2.A Quaternions and Euler angles for rotations""""Chapter 3 Image Formation""; ""3.1 Representation of images""; ""3.2 Lenses, light, and basic photometry""; ""3.3 A geometric model of image formation""; ""3.4 Summary""; ""3.5 Exercises""; ""3.A Basic photometry with light sources and surfaces""; ""3.B Image formation in the language of projective geometry""; ""Chapter 4 Image Primitives and Correspondence""; ""4.1 Correspondence of geometric features""; ""4.2 Local deformation models""; ""4.3 Matching point features""; ""4.4 Tracking line features""; ""4.5 Summary""; ""4.6 Exercises"" ""4.A Computing image gradients""""Part II Geometry of Two Views""; ""Chapter 5 Reconstruction from Two Calibrated Views""; ""5.1 Epipolar geometry""; ""5.2 Basic reconstruction algorithms""; ""5.3 Planar scenes and homography""; ""5.4 Continuous motion case""; ""5.5 Summary""; ""5.6 Exercises""; ""5.A Optimization subject to the epipolar constraint""; ""Chapter 6 Reconstruction from Two Uncalibrated Views""; ""6.1 Uncalibrated camera or distorted space?""; ""6.2 Uncalibrated epipolar geometry""; ""6.3 Ambiguities and constraints in image formation""; ""6.4 Strati ed reconstruction"" ""6.5 Calibration with scene knowledge""""6.6 Dinner with Kruppa""; ""6.7 Summary""; ""6.8 Exercises""; ""6.A From images to fundamental matrices""; ""6.B Properties of Kruppa's equations""; ""Chapter 7 Estimation of Multiple Motions from Two Views""; ""7.1 Multibody epipolar constraint and the fundamental matrix""; ""7.2 A rank condition for the number of motions""; ""7.3 Geometric properties of the multibody fundamental matrix""; ""7.4 Multibody motion estimation and segmentation""; ""7.5 Multibody structure from motion""; ""7.6 Summary""; ""7.7 Exercises"" ""7.A Homogeneous polynomial factorization""""Part III Geometry of Multiple Views""; ""Chapter 8 Multiple-View Geometry of Points and Lines""; ""8.1 Basic notation for the (pre)image and coimage of points and lines""; ""8.2 Preliminary rank conditions of multiple images""; ""8.3 Geometry of point features""; ""8.4 Geometry of line features""; ""8.5 Uncalibrated factorization and strati cation""; ""8.6 Summary""; ""8.7 Exercises""; ""8.A Proof for the properties of bilinear and trilinear constraints""; ""Chapter 9 Extension to General Incidence Relations""
Series Title: Interdisciplinary applied mathematics.

Abstract:

This book gives senior undergraduate and beginning graduate students and researchers in computer vision, applied mathematics, computer graphics, and robotics a self-contained introduction to the geometry of 3D vision; that is the reconstruction of 3D models of objects from a collection of 2D images. Following a brief introduction, Part I provides background materials for the rest of the book. The two fundamental transformations, namely rigid body motion and perspective projection are introduced and image formation and feature extraction discussed. Part II covers the classic theory of two view.

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