地球信息科学学报 ›› 2022, Vol. 24 ›› Issue (2): 365-377.doi: 10.12082/dqxxkx.2022.210313
汪文琪1,2(), 李宗春1,*(
), 付永健1, 熊峰1, 赵昭明1,3, 何华1
收稿日期:
2021-06-03
修回日期:
2021-07-04
出版日期:
2022-02-25
发布日期:
2022-04-25
通讯作者:
*李宗春(1973— ),男,山东日照人,博士,教授,主要从事精密工程测量、激光雷达点云数据处理研究。 E-mail: 13838092876@139.com作者简介:
汪文琪(1996— ),男,安徽宿州人,硕士,主要从事激光雷达点云数据处理研究。E-mail: wenqi_xd@163.com
WANG Wenqi1,2(), LI Zongchun1,*(
), FU Yongjian1, XIONG Feng1, ZHAO Zhaoming1,3, HE Hua1
Received:
2021-06-03
Revised:
2021-07-04
Online:
2022-02-25
Published:
2022-04-25
摘要:
单一基元分类方法难以全面描述复杂的点云场景,采用多基元进行分类成为一种趋势,提出了一种融合点、体素和对象特征的点云分类方法。主要包括4个方面:① 分别确定各层面分类基元,点基元方面采用最优邻域方法,体素基元方面基于八叉树方法进行体素划分,对象基元方面使用改进的多要素分割方法进行点云分割;② 提取各基元分类特征,首先提取点基元分类特征并进行局部线性约束编码(Locality-constrained Linear Coding, LLC),然后以此为基础提取体素基元和对象基元的潜在狄利克雷分布特征(Latent Dirichlet Allocation, LDA)和最大池化特征(Max Pooling, MP);③ 降低分类特征维度,利用随机森林变量重要性算法对分类特征进行筛选与降维;④ 进行点云分类,使用随机森林算法实现点云分类。采用3种不同类型的点云数据进行试验,结果表明融合3种基元特征的分类精度相比于点基元分类分别提升了1.43%、7.02%和2.48%,分类特征降维可以有效降低特征冗余度,分类器分类时间减少约70%;通过与其他算法的对比,新算法分类精度更优,且适用于多种场景点云数据的分类。
汪文琪, 李宗春, 付永健, 熊峰, 赵昭明, 何华. 融合点、体素和对象特征的多基元点云分类[J]. 地球信息科学学报, 2022, 24(2): 365-377.DOI:10.12082/dqxxkx.2022.210313
WANG Wenqi, LI Zongchun, FU Yongjian, XIONG Feng, ZHAO Zhaoming, HE Hua. The Multiple Primitives Classification of Point Cloud Combining Point, Voxel and Object Features[J]. Journal of Geo-information Science, 2022, 24(2): 365-377.DOI:10.12082/dqxxkx.2022.210313
表2
场景I分类结果
指标 | 类别 | |||
---|---|---|---|---|
植被 | 建筑 | 地面 | ||
R | 策略① | 96.79 | 84.81 | 96.41 |
策略② | 96.79 | 88.48 | 96.90 | |
策略③ | 97.66 | 92.57 | 96.88 | |
策略④ | 97.50 | 92.65 | 97.09 | |
P | 策略① | 96.49 | 88.04 | 95.85 |
策略② | 97.00 | 90.06 | 96.06 | |
策略③ | 97.33 | 94.72 | 96.75 | |
策略④ | 97.47 | 94.70 | 96.52 | |
F1 | 策略① | 96.64 | 86.40 | 96.13 |
策略② | 96.90 | 89.26 | 96.48 | |
策略③ | 97.50 | 93.63 | 96.81 | |
策略④ | 97.48 | 93.67 | 96.81 | |
OA | 策略① 95.43 策略② 95.98 策略③ 96.87 策略④ 96.86 |
表3
场景II分类结果
指标 | 类别 | ||||
---|---|---|---|---|---|
植被 | 建筑 | 地面 | 车辆 | ||
R | 策略① | 84.20 | 86.68 | 98.75 | 94.96 |
策略② | 91.87 | 93.34 | 99.26 | 98.09 | |
策略③ | 97.83 | 98.74 | 98.78 | 99.65 | |
策略④ | 97.93 | 98.73 | 99.12 | 99.57 | |
P | 策略① | 89.06 | 94.41 | 99.37 | 45.21 |
策略② | 96.25 | 97.17 | 99.34 | 60.82 | |
策略③ | 98.52 | 98.80 | 99.34 | 89.56 | |
策略④ | 98.71 | 99.04 | 99.42 | 89.80 | |
F1 | 策略① | 86.57 | 90.38 | 99.06 | 61.25 |
策略② | 94.01 | 95.22 | 99.30 | 75.09 | |
策略③ | 98.18 | 98.77 | 99.06 | 94.34 | |
策略④ | 98.32 | 98.88 | 99.27 | 94.43 | |
OA | 策略① 91.74 策略② 95.80 策略③ 98.60 策略④ 98.76 |
表4
场景III分类结果
指标 | 类别 | ||||
---|---|---|---|---|---|
植被 | 建筑 | 地面 | 电力线 | ||
R | 策略① | 83.28 | 97.63 | 97.65 | 94.76 |
策略② | 94.54 | 98.90 | 98.14 | 96.83 | |
策略③ | 98.17 | 99.30 | 98.19 | 97.75 | |
策略④ | 97.99 | 99.35 | 98.30 | 97.72 | |
P | 策略① | 84.60 | 97.02 | 98.66 | 96.43 |
策略② | 96.16 | 98.60 | 98.44 | 96.12 | |
策略③ | 99.84 | 99.05 | 98.34 | 98.09 | |
策略④ | 99.84 | 99.07 | 98.41 | 98.40 | |
F1 | 策略① | 83.94 | 97.32 | 98.15 | 95.58 |
策略② | 95.34 | 98.75 | 98.29 | 96.47 | |
策略③ | 98.99 | 99.18 | 98.25 | 97.92 | |
策略④ | 98.91 | 99.21 | 98.36 | 98.06 | |
OA | 策略① 96.47 策略② 98.34 策略③ 98.91 策略④ 98.95 |
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