Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method.udud
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机译：点云配准是多视图3D测量中的关键过程。其精度直接影响测量精度。然而，在点云具有非重叠区域或曲率不变的表面的情况下，难以实现高精度。提出了一种基于球体特征约束的高精度配准方法。一些已知的带有约束的球体特征用于构造虚拟重叠区域。虚拟重叠区域可提供更准确的对应点对并减少噪声的影响。然后利用权函数的优化方法求解配准点云之间的变换参数。在这种情况下，可以减少点云中大噪声的影响，并实现高精度配准。仿真和实验验证了该方法的有效性。 ud ud
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