A General and Effective Method for Wall and Protrusion Separation from Facade Point Clouds
As a critical prerequisite for semantic facade reconstruction, accurately separating wall and protrusion points from facade point clouds is required. The performance of traditional separation methods is severely limited by facade conditions, including wall shapes (e.g., nonplanar walls), wall compos...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2023-01-01
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| Series: | Journal of Remote Sensing |
| Online Access: | https://spj.science.org/doi/10.34133/remotesensing.0069 |
| _version_ | 1797742262048784384 |
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| author | Shangshu Cai Shuhang Zhang Wuming Zhang Hongchao Fan Jie Shao Guangjian Yan Sisi Yu Aiguang Li Guoqing Zhou |
| author_facet | Shangshu Cai Shuhang Zhang Wuming Zhang Hongchao Fan Jie Shao Guangjian Yan Sisi Yu Aiguang Li Guoqing Zhou |
| author_sort | Shangshu Cai |
| collection | DOAJ |
| description | As a critical prerequisite for semantic facade reconstruction, accurately separating wall and protrusion points from facade point clouds is required. The performance of traditional separation methods is severely limited by facade conditions, including wall shapes (e.g., nonplanar walls), wall compositions (e.g., walls composed of multiple noncoplanar point clusters), and protrusion structures (e.g., protrusions without regularity, repetitive, or self-symmetric features). This study proposes a more widely applicable wall and protrusion separation method. The major principle underlying the proposed method is to transform the wall and protrusion separation problem as a ground filtering problem and to separate walls and protrusions using ground filtering methods, since the 2 problems can be solved using the same prior knowledge, that is, protrusions (nonground objects) protrude from walls (ground). After transformation problem, cloth simulation filter was used as an example to separate walls and protrusions in 8 facade point clouds with various characteristics. The proposed method was robust to the facade conditions, with a mean intersection over union of 90.7%, and had substantially higher accuracy compared with the traditional separation methods, including region growing-, random sample consensus-, multipass random sample consensus-based, and hybrid methods, with mean intersection over union values of 69.53%, 49.52%, 63.93%, and 47.07%, respectively. Besides, the proposed method was general, since existing ground filtering methods (including the maximum slope, progressive morphology, and progressive triangular irregular network densification filters) can also perform well. |
| first_indexed | 2024-03-12T14:38:25Z |
| format | Article |
| id | doaj.art-ae868de036e14d79b2cca8987562d854 |
| institution | Directory Open Access Journal |
| issn | 2694-1589 |
| language | English |
| last_indexed | 2024-03-12T14:38:25Z |
| publishDate | 2023-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Journal of Remote Sensing |
| spelling | doaj.art-ae868de036e14d79b2cca8987562d8542023-08-17T00:12:07ZengAmerican Association for the Advancement of Science (AAAS)Journal of Remote Sensing2694-15892023-01-01310.34133/remotesensing.0069A General and Effective Method for Wall and Protrusion Separation from Facade Point CloudsShangshu Cai0Shuhang Zhang1Wuming Zhang2Hongchao Fan3Jie Shao4Guangjian Yan5Sisi Yu6Aiguang Li7Guoqing Zhou8School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou, China.School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou, China.School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou, China.Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, Norway.School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou, China.Faculty of Geographical Science, Beijing Normal University, Beijing, China.University of Chinese Academy of Sciences, Beijing, China.School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou, China.Guilin University of Technology, Guilin, China.As a critical prerequisite for semantic facade reconstruction, accurately separating wall and protrusion points from facade point clouds is required. The performance of traditional separation methods is severely limited by facade conditions, including wall shapes (e.g., nonplanar walls), wall compositions (e.g., walls composed of multiple noncoplanar point clusters), and protrusion structures (e.g., protrusions without regularity, repetitive, or self-symmetric features). This study proposes a more widely applicable wall and protrusion separation method. The major principle underlying the proposed method is to transform the wall and protrusion separation problem as a ground filtering problem and to separate walls and protrusions using ground filtering methods, since the 2 problems can be solved using the same prior knowledge, that is, protrusions (nonground objects) protrude from walls (ground). After transformation problem, cloth simulation filter was used as an example to separate walls and protrusions in 8 facade point clouds with various characteristics. The proposed method was robust to the facade conditions, with a mean intersection over union of 90.7%, and had substantially higher accuracy compared with the traditional separation methods, including region growing-, random sample consensus-, multipass random sample consensus-based, and hybrid methods, with mean intersection over union values of 69.53%, 49.52%, 63.93%, and 47.07%, respectively. Besides, the proposed method was general, since existing ground filtering methods (including the maximum slope, progressive morphology, and progressive triangular irregular network densification filters) can also perform well.https://spj.science.org/doi/10.34133/remotesensing.0069 |
| spellingShingle | Shangshu Cai Shuhang Zhang Wuming Zhang Hongchao Fan Jie Shao Guangjian Yan Sisi Yu Aiguang Li Guoqing Zhou A General and Effective Method for Wall and Protrusion Separation from Facade Point Clouds Journal of Remote Sensing |
| title | A General and Effective Method for Wall and Protrusion Separation from Facade Point Clouds |
| title_full | A General and Effective Method for Wall and Protrusion Separation from Facade Point Clouds |
| title_fullStr | A General and Effective Method for Wall and Protrusion Separation from Facade Point Clouds |
| title_full_unstemmed | A General and Effective Method for Wall and Protrusion Separation from Facade Point Clouds |
| title_short | A General and Effective Method for Wall and Protrusion Separation from Facade Point Clouds |
| title_sort | general and effective method for wall and protrusion separation from facade point clouds |
| url | https://spj.science.org/doi/10.34133/remotesensing.0069 |
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