Globally Optimal Least Squares Solutions for Quasiconvex 1D Vision Problems
Solutions to non-linear least squares problems play an essential role in structure and motion problems in computer vision. The predominant approach for solving these problems is a Newton like scheme which uses the: hessian of the function to iteratively find a, local solution. Although fast, this strategy inevitably leeds to issues with poor local minima, and missed global minima. In this paper ra
