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Extrinsic calibration of a non-overlapping camera network based on close-range photogrammetry

机译:基于近距离摄影测量的非重叠相机网络的外部校准

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摘要

In this paper, an extrinsic calibration method for a non-overlapping camera network is presented based on close-range photogrammetry. The method does not require calibration targets or the cameras to be moved. The visual sensors are relatively motionless and do not see the same area at the same time. The proposed method combines the multiple cameras using some arbitrarily distributed encoded targets. The calibration procedure consists of three steps: reconstructing the three-dimensional (3D) coordinates of the encoded targets using a hand-held digital camera, performing the intrinsic calibration of the camera network, and calibrating the extrinsic parameters of each camera with only one image. A series of experiments, including 3D reconstruction, rotation, and translation, are employed to validate the proposed approach. The results show that the relative error for the 3D reconstruction is smaller than 0.003%, the relative errors of both rotation and translation are less than 0.066%, and the re-projection error is only 0.09 pixels. (C) 2016 Optical Society of America
机译:本文提出了一种基于近距离摄影测量的非重叠相机网络的外在标定方法。该方法不需要校准目标或移动摄像机。视觉传感器相对静止不动,不会同时看到相同的区域。所提出的方法使用一些任意分布的编码目标来组合多个摄像机。校准过程包括三个步骤:使用手持数码相机重建编码目标的三维(3D)坐标,执行相机网络的固有校准以及仅用一个图像校准每个相机的外部参数。通过一系列实验,包括3D重建,旋转和平移,来验证所提出的方法。结果表明,3D重建的相对误差小于0.003%,旋转和平移的相对误差小于0.066%,重投影误差仅为0.09像素。 (C)2016美国眼镜学会

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