基于法矢的点云拼合方法

REGISTRATION METHOD FOR POINT CLOUDS BASED ON NORMAL VECTORS

提出一种新的点云拼合方法。该方法由高斯映射不变量寻找对应点,再根据对应点间刚体变换的聚类特性来剔除错误的对应关系。采用奇异值分解,通过迭代计算拼合的刚体变换。试验表明,采用高斯映射不变量寻找对应点比采用曲率更为有效,与传统的迭代最近点算法相比,所提出的方法能更好地解决部分重叠点云的拼合问题。

A novel registration method for point clouds is pre- sented, which consists of three main steps. Corresponding points are found through the invariants of Gaussian images. Some erroneous coincidence relationships are eliminated based on the clustering characteristic of rigid transformations between corresponding points. The rigid transformation of the registra- tion is obtained in an iterative process by using singular value decomposition. Experiments show that the invariants of Gaus- sian images are more effective in identifying corresponding points than curvatures. Compared with the traditional iterative closest point （ICP） algorithm, the proposed method is better to register partially overlapped point clouds.