Minghao Ruan, Daniel F. Huber
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引用次数: 39

摘要

随着相对低成本的实时3D成像传感器的出现,3D传感器套件的新应用正在变得可行。例如,工业机器人工作单元中的3D传感器可以监控工人的位置以确保他们的安全。本文介绍了一种简单易用的用于观测同一工作空间的多个三维传感器的外部标定方法。传统的平面目标相机标定技术不适合这种情况,因为多个相机可能无法观测到相同的目标。我们的方法使用手持球形目标,从工作空间内的不同点进行成像。该算法在一系列视图中自动检测球体,同时估计球体中心和外部参数,以对齐任意的三维传感器网络。我们用校准异构3D相机集合的示例演示了该方法,并获得了比传统的基于图像的校准更好的结果。
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Calibration of 3D Sensors Using a Spherical Target
With the emergence of relatively low-cost real-time 3D imaging sensors, new applications for suites of 3D sensors are becoming practical. For example, 3D sensors in an industrial robotic work cell can monitor workers' positions to ensure their safety. This paper introduces a simple-to-use method for extrinsic calibration of multiple 3D sensors observing a common workspace. Traditional planar target camera calibration techniques are not well-suited for such situations, because multiple cameras may not observe the same target. Our method uses a hand-held spherical target, which is imaged from various points within the workspace. The algorithm automatically detects the sphere in a sequence of views and simultaneously estimates the sphere centers and extrinsic parameters to align an arbitrary network of 3D sensors. We demonstrate the approach with examples of calibrating heterogeneous collections of 3D cameras and achieve better results than traditional, image-based calibration.
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