Riemannian Computing in Computer Vision

Riemannian Computing in Computer Vision edited by Pavan K. Turaga, Anuj Srivastava.

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 approa...

Full description

Saved in:
Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Turaga, Pavan K. (Editor), Srivastava, Anuj (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Series:Springer eBook Collection.
Subjects:
Signal processing.
Image processing.
Speech processing systems.
Optical data processing.
Applied mathematics.
Engineering mathematics.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Welcome to Riemannian Computing in Computer Vision
  • Recursive Computation of the Fŕechet 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.

Similar Items