Premium
Jacobi‐type Methods in Computer Vision: A Case Study
Author(s) -
Hüper K.,
Helmke U.
Publication year - 1998
Publication title -
zamm ‐ journal of applied mathematics and mechanics / zeitschrift für angewandte mathematik und mechanik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 51
eISSN - 1521-4001
pISSN - 0044-2267
DOI - 10.1002/zamm.19980781545
Subject(s) - convergence (economics) , orbit (dynamics) , type (biology) , function (biology) , computer science , matching (statistics) , stereopsis , computer vision , mathematical optimization , mathematics , artificial intelligence , engineering , ecology , statistics , aerospace engineering , evolutionary biology , economics , biology , economic growth
In this paper we study the problem of minimizing a least squares distance function on an orbit of a noncompact Lie group. Such a problem occurs in the computer vision area, e. g., the socalled stereo matching problem without correspondence can be formulated in such a way. A Jacobi‐type method is developed to minimize the smooth cost function over that orbit. The convergence properties of the algorithm are discussed.