An Accurate Method for Solving the PnL Problem Based on the Reprojection Error

Xie, Zhe; Hu, Jinlong; Peng, Dandan; Zhu, Guoli

doi:10.1109/m2vip58386.2023.10413408

2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) 2023

DOI: 10.1109/m2vip58386.2023.10413408

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An Accurate Method for Solving the PnL Problem Based on the Reprojection Error

Zhe Xie,

Jinlong Hu,

Dandan Peng

et al.

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2024

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Cited by 2 publications

References 19 publications

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Cylinder object 6-DOF pose estimation via single perspective circle on cylindrical surface

Yu,

Wang,

Guo

et al. 2024

Meas. Sci. Technol.

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Pose estimation is an important research topic in computer vision. In this paper, a novel method for six-degree-of-freedom (6-DOF) pose estimation of cylindrical objects via a single perspective circle on cylindrical surface is proposed. Unlike traditional methods that rely on planar circular features, a circular feature target which is affixed to the side of cylindrical objects is utilized. The geometric properties of the spatial curve formed by its contour are leveraged for pose estimation. Specifically, the imaging model of the spatial curve is established to derive the general equation of its projection curve. The initial pose is determined based on the perspective principle, and the final optimized pose is obtained with the least squares method. To avoid local optima, a verification and correction method is proposed to enhance estimation accuracy. Synthetic and physical experiments demonstrate that the proposed method can achieve real-time, high-precision pose estimation for cylindrical objects, exhibiting robustness against occlusion and noise interference.

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Cylinder object 6-DOF pose estimation via single perspective circle on cylindrical surface

Yu,

Wang,

Guo

et al. 2024

Meas. Sci. Technol.

View full text Add to dashboard Cite

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An Automatic Solution for Registration Between Single-Image and Point Cloud in Manhattan World Using Line Primitives

He,

Zou,

Zhai

et al. 2024

Remote Sensing

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2D-3D registration is increasingly being applied in various scientific and engineering scenarios. However, due to appearance differences and cross-modal discrepancies, it is demanding for image and point cloud registration methods to establish correspondences, making 2D-3D registration highly challenging. To handle these problems, we propose a novel and automatic solution for 2D-3D registration in Manhattan world based on line primitives, which we denote as VPPnL. Firstly, we derive the rotation matrix candidates by establishing the vanishing point coordinate system as the link of point cloud principal directions to camera coordinate system. Subsequently, the RANSAC algorithm, which accounts for the clustering of parallel lines, is employed in conjunction with the least-squares method for translation vectors estimation and optimization. Finally, a nonlinear least-squares graph optimization method is carried out to optimize the camera pose and realize the 2D-3D registration and point colorization. Experiments on synthetic data and real-world data illustrate that our proposed algorithm can address the problem of 2D-3D direct registration in the case of Manhattan scenes where images are limited and sparse.

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An Accurate Method for Solving the PnL Problem Based on the Reprojection Error

Cited by 2 publications

References 19 publications

Cylinder object 6-DOF pose estimation via single perspective circle on cylindrical surface

Cylinder object 6-DOF pose estimation via single perspective circle on cylindrical surface

An Automatic Solution for Registration Between Single-Image and Point Cloud in Manhattan World Using Line Primitives

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