关键词: 最近迭代点, 3D表面匹配, 空间相似变换, 不规则三角网, 共轭点

Abstract: In order to avoid the drawback of the traditional ICP (iteration closest point) method for co-registration, a non-linear least squares co-registration model is proposed, which is based on minimizing the sum of squares of the Euclidean distances between two overlapped surfaces. The experiments demonstrate that the proposed method can be used for the co-registration of cloud points collected by the airborne laser scanner, and the experimental results are comparable with those of traditional methods. The experimental results imply that the proposed method has a good performance for transformation parameters estimation in 3D point clouds co-registration procedure. Especially, the non-linear co-registration method can achieve the best estimated value with only 6 to 7 iteration time. It is much faster than traditional method in practice, and can be treated as an extension for traditional co-registration theory of iteration closest point in the field of computer vision.

Key words: ICP, 3D surface matching, 3D similarity transformation, triangulated irregular network, conjugate points