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Calibration of the Relative Orientation between Multiple Depth Cameras Based on a Three-Dimensional Target

机译:基于三维目标的多深度摄像机之间的相对取向的校准

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Depth cameras play a vital role in three-dimensional (3D) shape reconstruction, machine vision, augmented/virtual reality and other visual information-related fields. However, a single depth camera cannot obtain complete information about an object by itself due to the limitation of the camera’s field of view. Multiple depth cameras can solve this problem by acquiring depth information from different viewpoints. In order to do so, they need to be calibrated to be able to accurately obtain the complete 3D information. However, traditional chessboard-based planar targets are not well suited for calibrating the relative orientations between multiple depth cameras, because the coordinates of different depth cameras need to be unified into a single coordinate system, and the multiple camera systems with a specific angle have a very small overlapping field of view. In this paper, we propose a 3D target-based multiple depth camera calibration method. Each plane of the 3D target is used to calibrate an independent depth camera. All planes of the 3D target are unified into a single coordinate system, which means the feature points on the calibration plane are also in one unified coordinate system. Using this 3D target, multiple depth cameras can be calibrated simultaneously. In this paper, a method of precise calibration using lidar is proposed. This method is not only applicable to the 3D target designed for the purposes of this paper, but it can also be applied to all 3D calibration objects consisting of planar chessboards. This method can significantly reduce the calibration error compared with traditional camera calibration methods. In addition, in order to reduce the influence of the infrared transmitter of the depth camera and improve its calibration accuracy, the calibration process of the depth camera is optimized. A series of calibration experiments were carried out, and the experimental results demonstrated the reliability and effectiveness of the proposed method.
机译:深度摄像机在三维(3D)形状重建,机器视觉,增强/虚拟现实和其他相关领域中起着重要作用。然而,由于相机的视野的限制,单个深度摄像头本身无法自行获取完整的信息。多个深度摄像机可以通过从不同的视点获取深度信息来解决这个问题。为此,需要校准它们以便能够准确地获得完整的3D信息。然而,基于棋盘的平面目标不太适合校准多个深度相机之间的相对取向,因为不同深度摄像机的坐标需要统一到单个坐标系中,并且具有特定角度的多个相机系统具有非常小的重叠视野。在本文中,我们提出了一种基于3D目标的多个深度摄像机校准方法。 3D目标的每个平面用于校准独立的深度相机。 3D目标的所有平面都统一到单个坐标系中,这意味着校准平面上的特征点也在一个统一的坐标系中。使用此3D目标,可以同时校准多个深度相机。本文提出了一种使用LIDAR精确校准的方法。该方法不仅适用于为本文目的而设计的3D目标,但它也可以应用于由平面棋盘组成的所有3D校准对象。与传统的相机校准方法相比,此方法可以显着降低校准误差。另外,为了减少深度相机的红外发射器的影响,提高其校准精度,优化了深度相机的校准过程。进行了一系列校准实验,实验结果表明了所提出的方法的可靠性和有效性。

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