Title :
A globally convergent algorithm for minimizing over the rotation group of quadratic forms
Author :
Gurwitz, Chaya ; Overton, Michael L.
Author_Institution :
Dept. of Comput. & Inf. Sci., Brooklyn Coll., NY, USA
fDate :
11/1/1989 12:00:00 AM
Abstract :
The authors 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. It is demonstrate that the method is globally convergent
Keywords :
minimisation; quadratic programming; computer vision; convergence; globally convergent algorithm; minimisation; quadratic forms; rotation group; sequential quadratic programming; Computer science; Computer vision; Eigenvalues and eigenfunctions; Equations; Lagrangian functions; Null space; Quadratic programming; Symmetric matrices;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
