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A cylindrical shape descriptor for registration of unstructured point clouds from real-time 3D sensors

机译:来自实时3D传感器的非结构化点云注册的圆柱形描述符

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摘要

To deal with data sets from real-time 3D sensors of RGB-D or TOF cameras, this paper presents a method for registration of unstructured point clouds. We firstly derive intrinsic shape context descriptors for 3D data organization. To replace the Fast-Marching method, a vertex-oriented triangle propagation method is applied to calculate the 'angle' and 'radius' in descriptor charting, so that the matching accuracy at the twisting and folding area is significantly improved. Then, a 3D cylindrical shape descriptor is proposed for registration of unstructured point clouds. The chosen points are projected into the cylindrical coordinate system to construct the descriptors. The projection parameters are respectively determined by the distances from the chosen points to the reference normal vector, and the distances from the chosen points to the reference tangent plane and the projection angle. Furthermore, Fourier transform is adopted to deal with orientation ambiguity in descriptor matching. Practical experiments demonstrate a satisfactory result in point cloud registration and notable improvement on standard benchmarks.
机译:要从RGB-D或TOF相机的实时3D传感器处理数据集,本文介绍了非结构化点云注册的方法。我们首先派生3D数据组织的内在形状上下文描述符。为了更换快速行进的方法,应用面向顶点的三角形传播方法来计算描述符图中的“角度”和“半径”,从而显着提高了扭曲和折叠区域的匹配精度。然后,提出了一种用于注册非结构化点云的3D圆柱形描述符。所选择的点被投射到圆柱坐标系中以构造描述符。投影参数分别由从所选点到参考法向量的距离确定,以及从所选点到参考切线和投影角度的距离。此外,采用傅里叶变换来处理描述符匹配中的方向歧义。实际实验表明点云登记和标准基准的显着改善令人满意的结果。

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