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A new depth camera calibration algorithm

机译:一种新的深度相机校准算法

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摘要

Camera calibration constitutes a basic problem in many robot applications. In this paper two algorithms tailored to the calibration of the parameters of a depth camera are proposed. More precisely, a closed form solution that requires the coordinates of three corresponding points in the world and the camera coordinates systems, for the noise free case is proposed. Moreover, a robust algorithm that can be used for the successful estimation of the parameters in the presence of both uniform noise that models the quantization error along the axes of the “volume”, as well as of a sparse noise component for the modeling of large errors presented in depth measurements, is presented. From the simulation results we have obtained, the proposed methods seem to outperform in terms of the average worst case estimation errors frequently used algorithms for the problem at hand.
机译:相机校准是许多机器人应用中的基本问题。本文提出了两种适合深度相机参数校准的算法。更准确地说,针对无噪声的情况,提出了一种封闭形式的解决方案,该解决方案需要世界上三个对应点的坐标和相机坐标系。此外,一种健壮的算法可用于在沿“体积”轴对量化误差进行建模的均匀噪声以及对大型模型进行建模的稀疏噪声分量的存在下成功估算参数提出了深度测量中出现的误差。从我们获得的仿真结果来看,所提出的方法在解决当前最常见问题的算法的平均最坏情况估计误差方面似乎表现出色。

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