基于一致性球的点云配准算法研究

针对三维建模中经典ICP算法在点云重叠度低时配准精度不高的问题，提出一种基于一致性球的配准算法。该算法在寻找对应点方面，将球体的旋转不变性与基于邻域的SVD正交一致性算法结合起来，使得配准算法能够获得较高正确率的对应点，并以此为基础进行扩散，得到更多的对应点；再使用刚性约束对错误点对进行剔除，最后使用四元数法求解变换矩阵。该方法不仅克服了传统ICP配准算法的缺陷，而且精度也优于传统ICP配准算法。

Point Cloud Registration Algorithm Based on the Consistency of the Ball

In the field of 3D modeling, the precision of the traditional ICP algorithm is not high when the point cloud overlap is low, so we propose a registration algorithm based on consistent sphere. For the registration algorithm, on finding the corresponding points, the proposed algorithm innovatively combines the rotation invariance of the sphere with the SVD orthogonal consistency algorithm based on neighborhood. This helps the registration algorithm obtain the corresponding points with higher accuracy, and on this basis, spread and get more corresponding points. It then uses the rigid constraints to eliminate the error points. Finally, we use the quaternion method to solve transformation matrix. The results show that the proposed algorithm has not only overcome the shortcomings of the traditional ICP algorithm, but has better accuracy.