基于布料模拟滤波和随机森林的点云分类算法  

Point Clouds Classification Algorithm Based on Cloth Simulation Filtering and Random Forest

作　　者：郑津津[1] 于洋洋 周洪军[2] Zheng Jinjin

机构地区：[1]中国科学技术大学精密机械与精密仪器系,安徽合肥230026 [2]中国科学技术大学国家同步辐射实验室,安徽合肥230029

出　　处：《工业控制计算机》2020年第2期90-92,共3页Industrial Control Computer

基　　金：国家自然科学基金联合基金(GG2090090072,U1332130,U1713206);111引智工程(B07033);安徽省重点研究与开发计划(1704a0902051)。

摘　　要：提出了基于布料模拟滤波和随机森林的点云分类的方法。通过布料模拟滤波生成的地面点云进行高程值归一化,可以削减地形变化对点云分类精度的影响。对比未归一化结果,分类精度有30%的提升。把点云信息与遥感光谱信息融合进一步提高分类精度,对比其他分类结果有3%到5%的提升。This paper proposes a method based on cloth simulation filtering and point cloud classification of random forests.The effect of terrain change on the accuracy of point cloud classification can be reduced by normalizing elevation value by the ground point cloud generated by cloth simulation filtering.Compared with the unnormalized results,the classification accuracy is improved by 30%.The fusion of point cloud information with remote sensing spectral information is further improved.For other classification results there is a 3%to 5%increase.

关 键 词：布料模拟滤波 特征融合 点云分类 

分 类 号：TN713[电子电信—电路与系统] TN958.98