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Elastic shape analysis of three-dimensional objects / (Record no. 562285)

000 -LEADER
fixed length control field 09160nam a2200721 i 4500
001 - CONTROL NUMBER
control field 8047487
003 - CONTROL NUMBER IDENTIFIER
control field IEEE
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200413152925.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m eo d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cn |||m|||a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 171003s2017 caua foab 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781681730288
Qualifying information ebook
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9781681730271
Qualifying information print
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.2200/S00785ED1V01Y201707COV012
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number (CaBNVSL)swl00407816
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1005265191
040 ## - CATALOGING SOURCE
Original cataloging agency CaBNVSL
Language of cataloging eng
Description conventions rda
Transcribing agency CaBNVSL
Modifying agency CaBNVSL
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1637.5
Item number .J474 2017
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.693
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Jermyn, Ian H.,
Relator term author.
245 10 - TITLE STATEMENT
Title Elastic shape analysis of three-dimensional objects /
Statement of responsibility, etc. Ian H. Jermyn, Sebastian Kurtek, Hamid Laga, Anuj Srivastava.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture [San Rafael, California] :
Name of producer, publisher, distributor, manufacturer Morgan & Claypool,
Date of production, publication, distribution, manufacture, or copyright notice 2017.
300 ## - PHYSICAL DESCRIPTION
Extent 1 PDF (xv, 169 pages) :
Other physical details illustrations.
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term electronic
Source isbdmedia
338 ## - CARRIER TYPE
Carrier type term online resource
Source rdacarrier
490 1# - SERIES STATEMENT
Series statement Synthesis lectures on computer vision,
International Standard Serial Number 2153-1064 ;
Volume/sequential designation # 12
538 ## - SYSTEM DETAILS NOTE
System details note Mode of access: World Wide Web.
538 ## - SYSTEM DETAILS NOTE
System details note System requirements: Adobe Acrobat Reader.
500 ## - GENERAL NOTE
General note Part of: Synthesis digital library of engineering and computer science.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references (pages 155-165).
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Problem introduction and motivation -- 1.1 Problem area: 3D shape analysis -- 1.2 General goals and challenges -- 1.3 Past approaches and their limitations -- 1.4 Our approach: elastic shape analysis -- 1.5 Organization of this book -- 1.6 Notation --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 2. Elastic shape analysis: metrics and representations -- 2.1 Shapes -- 2.2 Elastic shape analysis -- 2.2.1 Encoding of registration -- 2.2.2 Riemannian metric and optimal registration -- 2.2.3 Geometric invariance -- 2.3 Background: elastic framework for curves -- 2.3.1 Elastic metric for curves -- 2.3.2 Geometric invariance -- 2.3.3 Summary of elastic framework for curves -- 2.4 Elastic framework for surfaces -- 2.4.1 Square-root map -- 2.4.2 Generalizing the elastic metric for curves -- 2.4.3 Elastic metric for surfaces -- 2.4.4 Reduced elastic metric: square-root normal field -- 2.4.5 Geometric invariance -- 2.4.6 SRNF inversion problem -- 2.5 Summary and next steps -- 2.6 Bibliographic notes --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 3. Computing geometrical quantities -- 3.1 Computing in shape space -- 3.1.1 Optimal registration and alignment -- 3.1.2 Optimal deformation -- 3.1.3 Putting it all together -- 3.1.4 Simplifying the computations using SRNFs -- 3.2 Registration and alignment using SRNFs -- 3.2.1 Optimization over the rotation group -- 3.2.2 Optimization over the reparameterization group -- 3.3 Geodesic computation techniques on general manifolds -- 3.3.1 Geodesic computation via path-straightening -- 3.3.2 Geodesic computation via shooting -- 3.4 Elastic geodesic paths between surfaces using pullback metrics -- 3.4.1 Path-straightening under pullback metrics -- 3.4.2 Shooting geodesics under SRNF pullback metric -- 3.5 Elastic geodesic paths between surfaces using SRNF inversion -- 3.5.1 Geodesics using SRNF inversion -- 3.5.2 Parallel transport in SRNF space -- 3.6 Elastic geodesic path examples -- 3.6.1 Discretization -- 3.6.2 Path-straightening -- 3.6.3 Shooting method -- 3.6.4 SRNF inversion -- 3.7 Summary and next steps -- 3.8 Bibliographic notes --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 4. Statistical analysis of shapes -- 4.1 Statistical summaries of 3D shapes -- 4.1.1 Pullback metric approach -- 4.1.2 SRNF inversion approach -- 4.2 Statistical models on shape spaces -- 4.2.1 Tangent space and pullback metric approach -- 4.2.2 SRNF inversion approach -- 4.3 Clustering and classification -- 4.4 Bibliographic notes --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 5. Case studies using human body and anatomical shapes -- 5.1 Clustering and classification -- 5.1.1 Attention deficit hyperactivity disorder (ADHD) classification -- 5.1.2 Clustering of identity and pose of human body shapes -- 5.2 Geodesic deformation -- 5.2.1 Geodesics -- 5.2.2 Deformation transfer -- 5.2.3 Reflection symmetry analysis and symmetrization -- 5.3 Statistical summaries of shapes -- 5.3.1 Means and modes of variation -- 5.3.2 Random sampling from shape models -- 5.4 Bibliographic notes --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note 6. Landmark-driven elastic shape analysis -- 6.1 Problem statement -- 6.2 Landmark-guided registration -- 6.2.1 Initial registration using landmarks -- 6.2.2 Registration using landmark-constrained diffeomorphisms -- 6.2.3 Landmark-constrained basis for registration -- 6.3 Elastic geodesics under landmark constraints -- 6.3.1 Illustration of geodesic paths -- 6.3.2 Evaluation of performance and computational cost -- 6.4 Landmark-constrained 3d shape atlas -- 6.5 Bibliographic notes --
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note A. Differential geometry -- Differentiable manifolds and tangent spaces -- Riemannian manifolds, geodesics, and the exponential map -- Geodesics -- Exponential map -- Lie group actions and quotient spaces -- B. Differential geometry of surfaces -- C. Spherical parametrization of triangulated meshes -- Conformal spherical mapping -- Coarse-to-fine minimal stretch embedding -- D. Landmark detection -- Landmark detection using heat kernel signatures -- Landmark correspondences -- Bibliography -- Authors' biographies.
506 ## - RESTRICTIONS ON ACCESS NOTE
Terms governing access Abstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0# - CITATION/REFERENCES NOTE
Name of source Compendex
510 0# - CITATION/REFERENCES NOTE
Name of source INSPEC
510 0# - CITATION/REFERENCES NOTE
Name of source Google scholar
510 0# - CITATION/REFERENCES NOTE
Name of source Google book search
520 3# - SUMMARY, ETC.
Summary, etc. Statistical analysis of shapes of 3D objects is an important problem with a wide range of applications. This analysis is difficult for many reasons, including the fact that objects differ in both geometry and topology. In this manuscript, we narrow the problem by focusing on objects with fixed topology, say objects that are diffeomorphic to unit spheres, and develop tools for analyzing their geometries. The main challenges in this problem are to register points across objects and to perform analysis while being invariant to certain shape-preserving transformations. We develop a comprehensive framework for analyzing shapes of spherical objects, i.e., objects that are embeddings of a unit sphere in R3 , including tools for: quantifying shape differences, optimally deforming shapes into each other, summarizing shape samples, extracting principal modes of shape variability, and modeling shape variability associated with populations. An important strength of this framework is that it is elastic: it performs alignment, registration, and comparison in a single unified framework, while being invariant to shape-preserving transformations. The approach is essentially Riemannian in the following sense. We specify natural mathematical representations of surfaces of interest, and impose Riemannian metrics that are invariant to the actions of the shape-preserving transformations. In particular, they are invariant to reparameterizations of surfaces. While these metrics are too complicated to allow broad usage in practical applications, we introduce a novel representation, termed square-root normal fields (SRNFs), that transform a particular invariant elastic metric into the standard L2 metric. As a result, one can use standard techniques from functional data analysis for registering, comparing, and summarizing shapes. Specifically, this results in: pairwise registration of surfaces; computation of geodesic paths encoding optimal deformations; computation of Karcher means and covariances under the shape metric; tangent Principal Component Analysis (PCA) and extraction of dominant modes of variability; and finally, modeling of shape variability using wrapped normal densities. These ideas are demonstrated using two case studies: the analysis of surfaces denoting human bodies in terms of shape and pose variability; and the clustering and classification of the shapes of subcortical brain structures for use in medical diagnosis. This book develops these ideas without assuming advanced knowledge in differential geometry and statistics. We summarize some basic tools from differential geometry in the appendices, and introduce additional concepts and terminology as needed in the individual chapters.
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE
Additional physical form available note Also available in print.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Title from PDF title page (viewed on October 3, 2017).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Three-dimensional imaging
General subdivision Mathematical models.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Elastography.
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term elastic Riemannian metric
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term shape model
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term shape metric
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term elastic registration
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term shape summary
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term modes of shape variability
655 #0 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Kurtek, Sebastian,
Dates associated with a name 1985-,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Laga, Hamid,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Srivastava, Anuj,
Dates associated with a name 1968-,
Relator term author.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
International Standard Book Number 9781681730271
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Synthesis digital library of engineering and computer science.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Synthesis lectures on computer vision ;
Volume/sequential designation # 12.
International Standard Serial Number 2153-1064
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified Abstract with links to resource
Uniform Resource Identifier http://ieeexplore.ieee.org/servlet/opac?bknumber=8047487
Holdings
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        PK Kelkar Library, IIT Kanpur PK Kelkar Library, IIT Kanpur 2020-04-13 EBKE785 2020-04-13 2020-04-13 E books

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