一种基于RANSAC 框架的椭球提取算法

面向点云数据，提出一种椭球的检测和提取算法。该算法采用随机采样一 致性（RANSAC）框架，通过多次随机采样点云模型，建立多个能够生成椭球体的最小点集， 对每个最小点集计算椭球参数，经过验证后建立椭球候选集合，利用分数函数评价各候选， 筛选出最佳提取椭球。实验结果表明：对于人工合成和扫描仪获取的点云数据，该算法稳定 可靠，可有效地提取出正确的椭球。

A RANSAC-based ellipsoid extraction algorithm

In this paper, an ellipsoid detection and extraction algorithm is proposed. The algorithm is designed and implemented based on the RANSAC (RANdom SAmpling Consensus) framework. Firstly, several minimum sets, one of which can define an ellipsoid, are selected from the point clouds by using random sampling strategy. Then, candidate set is formed from the effective ellipsoids, which come from the minimum sets and pass through the verification. Finally, the best approximate ellipsoids are extracted after the evaluation step using the score function. Experiments demonstrate that the algorithm is robust since it can effectively extract the ellipsoids from either manually synthesized point clouds or the raw data acquired by the scanners.