Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Beyond Gr\"obner Bases: Basis Selection for Minimal Solvers   Many computer vision applications require robust estimation of the underlying
geometry, in terms of camera motion and 3D structure of the scene. These robust
methods often rely on running minimal solvers in a RANSAC framework. In this
paper we show how we can make polynomial solvers based on the action matrix
method faster, by careful selection of the monomial bases. These monomial bases
have traditionally been based on a Gr\"obner basis for the polynomial ideal.
Here we describe how we can enumerate all such bases in an efficient way. We
also show that going beyond Gr\"obner bases leads to more efficient solvers in
many cases. We present a novel basis sampling scheme that we evaluate on a
number of problems.

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The categories of this paper are: gr-qc
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The categories of this paper are: econ
30
The categories of this paper are: q-alg
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The categories of this paper are: acc-phys
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The categories of this paper are: patt-sol
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-ex
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The categories of this paper are: atom-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: nlin
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The categories of this paper are: dg-ga
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The categories of this paper are: quant-ph
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The categories of this paper are: physics
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The categories of this paper are: chao-dyn