Uncertainty characterization of the orthogonal Procrustes problem with arbitrary covariance matrices

نویسندگان

Pedro Lourenço

Bruno Joao Nogueira Guerreiro

Pedro Tiago Martins Batista

Paulo Jorge Ramalho Oliveira

Carlos Silvestre

چکیده

This paper addresses the weighted orthogonal Procrustes problem of matching stochastically perturbed point clouds, formulated as an optimization problem with a closed-form solution. A novel uncertainty characterization of the solution of this problem is proposed resorting to perturbation theory concepts, which admits arbitrary transformations between point clouds and individual covariance and crosscovariance matrices for the points of each cloud. The method is thoroughly validated through extensive Monte Carlo simulations, and particularly interesting cases where nonlinearities may arise are further analyzed. & 2016 Elsevier Ltd. All rights reserved.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On a sub-Stiefel Procrustes problem arising in computer vision

In this paper we consider a Procrustes problem on the set of sub-Stiefel matrices. A sub-Stiefel matrix is a matrix that results from deleting simultaneously the last row and the last column of an orthogonal matrix. An iterative algorithm for computing the solution of the sub-Stiefel Procrustes problem is proposed. For these purposes we investigate the properties of sub-Stiefel matrices. We als...

متن کامل

Continuous Relaxations for the Traveling Salesman Problem

In this work, we construct heuristic approaches for the traveling salesman problem (TSP) based on embedding the discrete optimization problem into continuous spaces. We explore multiple embedding techniques – namely, the construction of dynamical flows on the manifold of orthogonal matrices and associated Procrustes approximations of the TSP cost function. In particular, we find that the Procru...

متن کامل

The Procrustes Problem for Orthogonal Stiefel Matrices

In this paper we consider the Procrustes problem on the manifold of orthogonal Stiefel matrices. Given matrices A 2 R mk , B 2 R mp , m p k, we seek the minimum of kA?BQk 2 for all matrices Q 2 R pk , Q T Q = I kk. We introduce a class of relaxation methods for generating minimizing sequences and ooer a geometric interpretation of these methods. Results of numerical experiments illustrating the...

متن کامل

Disentangling Two Orthogonal Matrices

Motivated by a certain molecular reconstruction methodology in cryo-electron microscopy, we consider the problem of solving a linear system with two unknown orthogonal matrices, which is a generalization of the well-known orthogonal Procrustes problem. We propose an algorithm based on a semi-definite programming (SDP) relaxation, and give a theoretical guarantee for its performance. Both theore...

متن کامل