Globally Optimal Estimates for Geometric Reconstruction Problems
作者:Fredrik Kahl, Didier Henrion
摘要
We introduce a framework for computing statistically optimal estimates of geometric reconstruction problems. While traditional algorithms often suffer from either local minima or non-optimality—or a combination of both—we pursue the goal of achieving global solutions of the statistically optimal cost-function.
论文关键词:non-convex optimization, structure from motion, triangulation, LMI relaxations, global optimization, semidefinite programming
论文评审过程:
论文官网地址:https://doi.org/10.1007/s11263-006-0015-y