基于多结构快速生成算法的建筑物平面提取

针对RANSAC算法在多结构数据集中提取平面点时存在的不足，提出了基于多结构快速生成算法的点云平面提取的新算法.该算法在随机产生一组平面模型之后，通过每个点相对于模型的残差排序信息，计算条件内点概率分布，然后利用得到的内点先验分布概率指导模型采样.实验结果表明，该算法能准确地检测出点云数据中的平面，相比RANSAC算法具有更好的采样效率.

The Extraction of the Plane of Building Based on Accelerating Hypothesis Generation for Multi-structure

This paper analyzed the deficiency of RANSAC that applying to the mutil-structure data set, then a plane fitting algorithm based on accelerating hypothesis generation for mutil-strueture algorithm is pro- posed. Firstly, the proposed method uses random sampling to generate a set of models. For each model, all pixels have been sorted by calculating their residuals. As a consequence, the sampling process is guided by the inlier conditional probability distribution, which is calculated by residual sorts of each model. The experi- mental results show that the proposed method can accurately extract planes from LIDAR point cloud and it can obtain higher efficiency of sampling than the RANSAC.