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Frequency domain point cloud registration based on the Fourier transform

机译:基于傅立叶变换的频域点云配准

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摘要

Due to the limited measurement range and occlusion of single-line structured light, it is impossible to detect the side data of the whole part. It is proposed that point cloud registration method obtained from multiple rotations of parts in frequency domain by Fourier transform. In the process of point cloud registration, cross-section point cloud data are restored to the corresponding size matrix firstly. Secondly, Fourier transform is carried out to calculate the point cloud data. When calculating the rotation angle, the polar coordinate transformation is carried out at first, and then the cross power spectrum of the two matrices is obtained, so that the rotation and translation matrix of the point cloud can also be obtained. In this process, considering point cloud noise existence, the Sinc function is approximately replaced by the non-noise inverse Fourier transform of cross power spectrum, so that the noise has no influence on the determination of registration parameters in frequency domain registration. The registration accuracy of point cloud is checked by high precision rotation and multiple measurements of mobile platform. Finally, the rotation matrix and translation values are obtained. (C) 2019 Published by Elsevier Inc.
机译:由于有限的测量范围和单线结构光的遮挡,无法检测整个零件的侧面数据。提出了通过傅立叶变换从频域中的零件多次旋转获得的点云配准方法。在点云配准过程中,首先将横截面点云数据恢复为相应的尺寸矩阵。其次,进行傅立叶变换计算点云数据。在计算旋转角度时,首先进行极坐标变换,然后获得两个矩阵的互功率谱,从而也可以获得点云的旋转和平移矩阵。在此过程中,考虑到点云噪声的存在,Sinc函数被互功率谱的非噪声逆傅立叶变换近似替代,因此该噪声对频域配准中配准参数的确定没有影响。点云的配准精度通过高精度旋转和移动平台的多次测量来检查。最后,获得旋转矩阵和平移值。 (C)2019由Elsevier Inc.发布

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