激光与光电子学进展, 2019, 56 (14): 142801, 网络出版: 2019-07-12
基于曲率分级的点云数据压缩方法 
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Curvature-Grading-Based Compression for Point Cloud Data
图 & 表
图 1. 点云1及其点数关于曲率的分布。 (a)点云1;(b)点数-曲率分布
Fig. 1. Point cloud 1 and point number-curvature distribution. (a) Point cloud 1; (b) point number-curvature distribution
图 2. 点云2及其点数关于曲率的分布。(a)点云2;(b)点数-曲率分布
Fig. 2. Point cloud 2 and point number-curvature distribution. (a) Point cloud 2; (b) point number-curvature distribution
图 6. 压缩前点云数据与3种压缩方法的压缩结果。(a)原始点云数据;(b) Geomagic软件压缩结果;(c)文献[ 8]中的方法压缩结果;(d)所提方法压缩结果
Fig. 6. Cloud data before compression and the results of three compression methods. (a) Original data; (b) compression result using Geomagic software; (c) compression result using the method in Ref. [8]; (d) compression result using the method proposed in this paper
图 7. 某局部区域与不同压缩率下的压缩结果。 (a)局部原始数据;(b)压缩率70%,S=53.0; (c)压缩率80%,S=10.5;(d)压缩率90%, S=1.1
Fig. 7. A local area and compression results under different compression ratios. (a) Original data of a local area; (b) compression ratio 70%, S=53.0; (c) compression ratio 80%, S=10.5; (d) compression ratio 90%, S=1.1
图 8. 压缩前与3种方法压缩后构建的表面模型。(a)原始数据构建的模型;(b) Geomagic软件压缩后构建的模型;(c)文献[ 8]中的方法压缩后构建的模型;(d)所提方法压缩后构建的模型
Fig. 8. Surface model built before compression and after compression by three methods. (a) Model built from original data; (b) model built from result compressed by Geomagic software; (c) model built from result compressed by the method in Ref. [8]; (d) model built from result compressed by the method proposed in this paper
表 1不同阈值的压缩结果
Table1. Compression results of different thresholds
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表 2不同压缩方法面积变化对比
Table2. Comparison of area changes of different compression methods
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李金涛, 程效军, 杨泽鑫, 杨荣淇. 基于曲率分级的点云数据压缩方法[J]. 激光与光电子学进展, 2019, 56(14): 142801. Jintao Li, Xiaojun Cheng, Zexin Yang, Rongqi Yang. Curvature-Grading-Based Compression for Point Cloud Data[J]. Laser & Optoelectronics Progress, 2019, 56(14): 142801.
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