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Riemannian computing in computer vision [electronic resource]

Riemannian computing in computer vision [electronic resource]

Material type
E-Book(소장)
Personal Author
Turaga, Pavan. Srivastava, Anuj, 1968-.
Title Statement
Riemannian computing in computer vision [electronic resource] / Pavan K. Turaga, Anuj Srivastava, editors.
Publication, Distribution, etc
Cham :   Springer International Publishing :   Imprint: Springer,   2016.  
Physical Medium
1 online resource (vi, 391 p.) : ill. (some col.).
ISBN
9783319229577
요약
This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approaches in problems such as face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion. Some of the mathematical entities that necessitate a geometric analysis include rotation matrices (e.g. in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours). Illustrates Riemannian computing theory on applications in computer vision, machine learning, and robotics. Emphasis on algorithmic advances that will allow re-application in other contexts. Written by leading researchers in computer vision and Riemannian computing, from universities and industry.
General Note
Title from e-Book title page.  
Content Notes
Welcome to Riemannian Computing in Computer Vision -- Recursive Computation of the Fr´echet Mean on Non-Positively Curved Riemannian Manifolds with Applications -- Kernels on Riemannian Manifolds -- Canonical Correlation Analysis on SPD(n) manifolds -- Probabilistic Geodesic Models for Regression and Dimensionality Reduction on Riemannian Manifolds -- Robust Estimation for Computer Vision using Grassmann Manifolds -- Motion Averaging in 3D Reconstruction Problems -- Lie-Theoretic Multi-Robot Localization -- CovarianceWeighted Procrustes Analysis -- Elastic Shape Analysis of Functions, Curves and Trajectories -- Why Use Sobolev Metrics on the Space of Curves -- Elastic Shape Analysis of Surfaces and Images -- Designing a Boosted Classifier on Riemannian Manifolds -- A General Least Squares Regression Framework on Matrix Manifolds for Computer Vision -- Domain Adaptation Using the Grassmann Manifold -- Coordinate Coding on the Riemannian Manifold of Symmetric Positive Definite Matrices for Image Classification -- Summarization and Search over Geometric Spaces.
Bibliography, Etc. Note
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Computer vision. Geometry, Riemannian.
Short cut
URL
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008 200414s2016 sz a ob 001 0 eng d
020 ▼a 9783319229577
040 ▼a 211009 ▼c 211009 ▼d 211009
050 4 ▼a TA1637-1638
082 0 4 ▼a 006.37 ▼2 23
084 ▼a 006.37 ▼2 DDCK
090 ▼a 006.37
245 0 0 ▼a Riemannian computing in computer vision ▼h [electronic resource] / ▼c Pavan K. Turaga, Anuj Srivastava, editors.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2016.
300 ▼a 1 online resource (vi, 391 p.) : ▼b ill. (some col.).
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references and index.
505 0 ▼a Welcome to Riemannian Computing in Computer Vision -- Recursive Computation of the Fr´echet Mean on Non-Positively Curved Riemannian Manifolds with Applications -- Kernels on Riemannian Manifolds -- Canonical Correlation Analysis on SPD(n) manifolds -- Probabilistic Geodesic Models for Regression and Dimensionality Reduction on Riemannian Manifolds -- Robust Estimation for Computer Vision using Grassmann Manifolds -- Motion Averaging in 3D Reconstruction Problems -- Lie-Theoretic Multi-Robot Localization -- CovarianceWeighted Procrustes Analysis -- Elastic Shape Analysis of Functions, Curves and Trajectories -- Why Use Sobolev Metrics on the Space of Curves -- Elastic Shape Analysis of Surfaces and Images -- Designing a Boosted Classifier on Riemannian Manifolds -- A General Least Squares Regression Framework on Matrix Manifolds for Computer Vision -- Domain Adaptation Using the Grassmann Manifold -- Coordinate Coding on the Riemannian Manifold of Symmetric Positive Definite Matrices for Image Classification -- Summarization and Search over Geometric Spaces.
520 ▼a This book presents a comprehensive treatise on Riemannian geometric computations and related statistical inferences in several computer vision problems. This edited volume includes chapter contributions from leading figures in the field of computer vision who are applying Riemannian geometric approaches in problems such as face recognition, activity recognition, object detection, biomedical image analysis, and structure-from-motion. Some of the mathematical entities that necessitate a geometric analysis include rotation matrices (e.g. in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours). Illustrates Riemannian computing theory on applications in computer vision, machine learning, and robotics. Emphasis on algorithmic advances that will allow re-application in other contexts. Written by leading researchers in computer vision and Riemannian computing, from universities and industry.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Computer vision.
650 0 ▼a Geometry, Riemannian.
700 1 ▼a Turaga, Pavan.
700 1 ▼a Srivastava, Anuj, ▼d 1968-.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-22957-7
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 006.37 Accession No. E14020428 Availability Loan can not(reference room) Due Date Make a Reservation Service M

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