Sylvester形式を用いた高効率な閉形式ポーズ推定手法
Efficient closed-form approaches for pose estimation using Sylvester forms
ポーズ推定の非線形最小二乗問題を多項式系に帰着させ、Sylvester形式を用いた閉形式解法を提案し、計算時間を短縮しつつ精度を維持することを示した。
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著者: Jana Vráblíková, Ezio Malis, Laurent Busé
分類: cs.CV, cs.RO
原文アブストラクト
Solving non-linear least-squares problem for pose estimation (rotation and translation) is often a time consuming yet fundamental problem in several real-time computer vision applications. With an adequate rotation parametrization, the optimization problem can be reduced to the solution of a~system of polynomial equations and solved in closed form. Recent advances in efficient closed form solvers utilizing resultant matrices have shown a promising research direction to decrease the computation time while preserving the estimation accuracy. In this paper, we propose a new class of resultant-based solvers that exploit Sylvester forms to further reduce the complexity of the resolution. We demonstrate that our proposed methods are numerically as accurate as the state-of-the-art solvers, and outperform them in terms of computational time. We show that this approach can be applied for pose estimation in two different types of problems: estimating a pose from 3D to 3D correspondences, and estimating a pose from 3D points to 2D points correspondences.
