Efficient reduction of L-infinity geometry problems

Hongdong Li
2009 2009 IEEE Conference on Computer Vision and Pattern Recognition  
This paper presents a new method for computing optimal L∞ solutions for vision geometry problems, particularly for those problems of fixed-dimension and of large-scale. Our strategy for solving a large L∞ problem is to reduce it to a finite set of smallest possible subproblems. By using the fact that many of the problems in question are pseudoconvex, we prove that such a reduction is possible. To actually solve these small subproblems efficiently, we propose a direct approach which makes no use
more » ... which makes no use of any convex optimizer (e.g. SOCP or LP), but is based on a simple local Newton method. We give both theoretic justification and experimental validation to the new method. Potentially, our new method can be made extremely fast.
doi:10.1109/cvpr.2009.5206653 dblp:conf/cvpr/Li09 fatcat:2ijjbyvhcbhlvjofjt66hsdgaa