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Optimizing Polynomial Solvers For Minimal Geometry Problems - Cis Upenn
Get Optimizing Polynomial Solvers For Minimal Geometry Problems - Cis Upenn
Nomial solvers based on algebraic geometry techniques, and specifically the action matrix method, have become popular for solving minimal problems in computer vision. In this paper we develop a new method for reducing the computational time and improving numerical stability of algorithms using this method. To achieve this, we propose and prove a set of algebraic conditions which allow us to reduce the size of the elimination template (polynomial coefficient matrix), which leads to faster LU or Q.
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