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.

为了处理来自RGB-D或TOF相机的实时3D传感器的数据集，本文提出了一种用于注册非结构化点云的方法。我们首先导出3D数据组织的固有形状上下文描述符。为了替代快速前进方法，使用了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”，从而显着提高了在扭曲和折叠区域的匹配精度。然后，提出了一种3D圆柱形状描述符，用于非结构化点云的配准。选定的点将投影到圆柱坐标系中以构造描述符。投影参数分别由所选点到参考法线矢量的距离确定，以及从选定点到参考切线平面的距离以及投影角度。此外，采用傅里叶变换来处理描述符匹配中的方位歧义。实际实验表明，在点云配准方面令人满意的结果以及对标准基准的显着改进。