<--- Back to Details
First PageDocument Content
Homography / Projective geometry / Transformation / Singular value decomposition / Algebra / Geometry / Mathematics
Date: 2007-02-21 00:44:35
Homography
Projective geometry
Transformation
Singular value decomposition
Algebra
Geometry
Mathematics

Add to Reading List

Source URL: cseweb.ucsd.edu

Download Document from Source Website

File Size: 66,83 KB

Share Document on Facebook

Similar Documents

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods Lecture: 1 The Singular Value Decomposition Instructor: Sham Kakade

DocID: 1vbS6 - View Document

Sampling Algorithms to Update Truncated SVD Ichitaro Yamazaki, Stanimire Tomov, and Jack Dongarra University of Tennessee, Knoxville, Tennessee, U.S.A. Abstract— A truncated singular value decomposition (SVD) is a powe

DocID: 1udU9 - View Document

Orthogonal Matrices and the Singular Value Decomposition Carlo Tomasi The first Section below extends to m × n matrices the results on orthogonality and projection we have previously seen for vectors. The Sections there

DocID: 1tr0F - View Document

Using Singular Value Decomposition to Parameterize State-Dependent Model Errors Christopher M. Danforth∗ Department of Mathematics and Statistics, University of Vermont Burlington, VTEugenia Kalnay

DocID: 1tjbW - View Document

CS168: The Modern Algorithmic Toolbox Lecture #9: The Singular Value Decomposition (SVD) and Low-Rank Matrix Approximations Tim Roughgarden & Gregory Valiant∗ April 25, 2016

DocID: 1rHEk - View Document