基于支持向量机的点云切片分割技术的研究

Research on point clouds section division technology based on support vector machine

支持向量机这种学习方法,最初用于处理模式识别问题,随后推广到解决回归估计问题,成功解决了高维问题和局部极值问题,是一个具有最优泛化能力的学习机器。提出了一种基于支持向量机最优超平面的点云切片分割技术,该技术采用较新的人工智能技术支持向量机(SVM)的最优超平面原理,应用其统计特性,把切片中的点分割成模型本身的独立部分。实验证明,该方法具有速度快、分割准确的优点,分割效果较好。

Support Vector Machine （SVM） is a study method. It was used in Pattern Recognition and then in regression. After High-dimensional problems and Local maximum problems are solved, it becomes an optimal generalization ability study machine. A method of point clouds section division technology based on support vector machine is presented. The new technology support vector machine and its excellent statistic characteristics are used to divide point clouds sections. Through the experiment, a nice effect is acquired, with the benefits of excellent error accuracy, high efficiency.