We propose a new method for constructing elimination templates for efficient
polynomial system solving of minimal problems in structure from motion, image
matching, and camera tracking. We first construct a particular affine
parameterization of the elimination templates for systems with a finite number
of distinct solutions. Then, we use a heuristic greedy optimization strategy
over the space of parameters to get a template with a small size. We test our
method on 34 minimal problems in computer vision. For all of them, we found the
templates either of the same or smaller size compared to the state-of-the-art.
For some difficult examples, our templates are, e.g., 2.1, 2.5, 3.8, 6.6 times
smaller. For the problem of refractive absolute pose estimation with unknown
focal length, we have found a template that is 20 times smaller. Our
experiments on synthetic data also show that the new solvers are fast and
numerically accurate. We also present a fast and numerically accurate solver
for the problem of relative pose estimation with unknown common focal length
and radial distortion.

提出了一种新的构造消元模板的方法，以解决最小化问题的多项式系统的高效求解，在计算机视觉中应用广泛，能够显著减少求解方法的时间和空间复杂度。