A Globally Convergent Algorithm for Minimizing Over the Rotation Group of Quadratic Forms

Chaya Gurwitz; Michael L. Overton

doi:10.1109/34.42863

A Globally Convergent Algorithm for Minimizing Over the Rotation Group of Quadratic Forms

Research output: Contribution to journal › Article › peer-review

Abstract

We describe a numerical procedure for solving problems involving minimization over the rotation group of quadratic forms which arise in connection with problems of computer vision. The algorithm presented is a sequential quadratic programming method which takes advantage of the special structure of the problem constraints. We conclude by proving that our method is globally convergent.

Original language	English (US)
Pages (from-to)	1228-1232
Number of pages	5
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	11
Issue number	11
DOIs	https://doi.org/10.1109/34.42863
State	Published - Nov 1989

Keywords

Nonlinear programming
projected Hessian
quadratic forms
rotation groups
sequential quadratic programming

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Artificial Intelligence
Applied Mathematics

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10.1109/34.42863

Cite this

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abstract = "We describe a numerical procedure for solving problems involving minimization over the rotation group of quadratic forms which arise in connection with problems of computer vision. The algorithm presented is a sequential quadratic programming method which takes advantage of the special structure of the problem constraints. We conclude by proving that our method is globally convergent.",

keywords = "Nonlinear programming, projected Hessian, quadratic forms, rotation groups, sequential quadratic programming",

author = "Chaya Gurwitz and Overton, {Michael L.}",

year = "1989",

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A Globally Convergent Algorithm for Minimizing Over the Rotation Group of Quadratic Forms

Abstract

Keywords

ASJC Scopus subject areas

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