Book 2016

Riemannian Computing in Computer Vision

Editors:

ISBN: 978-3-319-22956-0 (Print) 978-3-319-22957-7 (Online)

Table of contents (17 chapters)

  1. Front Matter

    Pages i-vi

  2. No Access

    Chapter

    Pages 1-18

    Welcome to Riemannian Computing in Computer Vision

  3. Statistical Computing on Manifolds

    1. Front Matter

      Pages 19-19

    2. No Access

      Chapter

      Pages 21-43

      Recursive Computation of the Fréchet Mean on Non-positively Curved Riemannian Manifolds with Applications

    3. No Access

      Chapter

      Pages 45-67

      Kernels on Riemannian Manifolds

    4. No Access

      Chapter

      Pages 69-100

      Canonical Correlation Analysis on SPD(n) Manifolds

    5. No Access

      Chapter

      Pages 101-121

      Probabilistic Geodesic Models for Regression and Dimensionality Reduction on Riemannian Manifolds

  4. Color, Motion, and Stereo

    1. Front Matter

      Pages 123-123

    2. No Access

      Chapter

      Pages 125-144

      Robust Estimation for Computer Vision Using Grassmann Manifolds

    3. No Access

      Chapter

      Pages 145-164

      Motion Averaging in 3D Reconstruction Problems

    4. No Access

      Chapter

      Pages 165-186

      Lie-Theoretic Multi-Robot Localization

  5. Shapes, Surfaces, and Trajectories

    1. Front Matter

      Pages 187-187

    2. No Access

      Chapter

      Pages 189-209

      Covariance Weighted Procrustes Analysis

    3. No Access

      Chapter

      Pages 211-231

      Elastic Shape Analysis of Functions, Curves and Trajectories

    4. No Access

      Chapter

      Pages 233-255

      Why Use Sobolev Metrics on the Space of Curves

    5. No Access

      Chapter

      Pages 257-277

      Elastic Shape Analysis of Surfaces and Images

  6. Objects, Humans, and Activity

    1. Front Matter

      Pages 279-279

    2. No Access

      Chapter

      Pages 281-301

      Designing a Boosted Classifier on Riemannian Manifolds

    3. No Access

      Chapter

      Pages 303-323

      A General Least Squares Regression Framework on Matrix Manifolds for Computer Vision

    4. No Access

      Chapter

      Pages 325-343

      Domain Adaptation Using the Grassmann Manifold

    5. No Access

      Chapter

      Pages 345-361

      Coordinate Coding on the Riemannian Manifold of Symmetric Positive-Definite Matrices for Image Classification

    6. No Access

      Chapter

      Pages 363-387

      Summarization and Search Over Geometric Spaces

  7. Back Matter

    Pages 389-391