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A Stable Algebraic Camera Pose Estimation for Minimal Configurations of 2D/3D Point and Line Correspondences

机译:2D / 3D点和线对应的最小配置的稳定代数摄像机姿态估计

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This paper proposes an algebraic solution for the problem of camera pose estimation using the minimal configurations of 2D/3D point and line correspondences, including three point correspondences, two point and one line correspondences, one point and two line correspondences, and three line correspondences. In contrast to the previous works that address these problems in specific geometric ways, this paper shows that the above four cases can be solved in a generic algebraic-framework. Specifically, the orientation of the camera is computed from a polynomial equation system of four quadrics, then the translation can be solved from a linear equation system. To make our algorithm stable, the key is the polynomial solver. We significantly improve the numerical stability of the efficient three quadratic equation system solver, E3Q3 [17], with a slight computational cost. The simulation results show that the numerical stability of our algorithm is comparable to the state-of-the-art Perspective-3-Point (P3P) algorithm [14], and outperforms the state-of-the-art algorithms of the other three cases. The numerical stability of our algorithm can be further improved by a rough estimation of the rotation matrix, which is generally available in the Localization and Mapping (SLAM) or Visual Odometry (VO) system (such as the pose from the last frame). Besides, this algorithm is applicable to real-time applications.
机译:本文提出了一种使用2D / 3D点和线对应的最小配置来解决相机姿态估计问题的代数解决方案,包括三点对应,两点和一线对应,一点和两线对应以及三线对应。与以前以特定的几何方式解决这些问题的著作相反,本文表明可以在通用代数框架中解决以上四种情况。具体地,从四个二次方程式的多项式方程组计算出摄像机的方位,然后可以从线性方程组求解平移。为了使我们的算法稳定,关键是多项式求解器。我们以少量的计算成本,显着提高了有效的三个二次方程系统求解器E3Q3的数值稳定性[17]。仿真结果表明,我们算法的数值稳定性可与最新的Perspective-3-Point(P3P)算法相媲美[14],并优于其他三个算法的最新算法。案件。通过对旋转矩阵进行粗略估计,可以进一步提高算法的数值稳定性,该估计通常可在“定位和映射(SLAM)”或“视觉Odometry(VO)”系统中使用(例如最后一帧的姿态)。此外,该算法适用于实时应用。

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