Baoyun Guo
Biographic Data
| ID | 9834867 |
|---|---|
| NAME | Baoyun Guo |
| GIVEN NAMES | Baoyun |
| FAMILY NAME | Guo |
| SIGNATURE | GUO B |
| AFFILIATIONS | Shandong University of Technology |
| ORCID | 0000-0001-5413-2816 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Airborne LiDAR Point Cloud Building Reconstruction Based on Planar Optimal Combination and Feature Line Constraints
This paper proposes a building reconstruction framework for airborne LiDAR data to address the challenge of automated modeling under conditions of uneven point cloud density and missing vertical walls, generating high-precision and structurally compact 3D building models. The method first combines adaptive resolution hypervoxels with a global graph cut optimization strategy to extract precise roof plane primitives from sparse point clouds of buil…
POI Data Fusion Method Based on Multi-Feature Matching and Optimization
The key to geospatial data integration lies in identifying corresponding objects from different sources. Aiming at the problem of the low matching accuracy of geospatial entities under a single feature attribute, a geospatial entity matching method based on multi-feature value calculation is proposed. Firstly, when dealing with POI (point of interest) data, the similarity of POI data in terms of name, address, and distance is calculated by combin…
Semantic Segmentation and Roof Reconstruction of Urban Buildings Based on LiDAR Point Clouds
In urban point cloud scenarios, due to the diversity of different feature types, it becomes a primary challenge to effectively obtain point clouds of building categories from urban point clouds. Therefore, this paper proposes the Enhanced Local Feature Aggregation Semantic Segmentation Network (ELFA-RandLA-Net) based on RandLA-Net, which enables ELFA-RandLA-Net to perceive local details more efficiently by learning geometric and semantic features…
No prominent works on this page.
Semantic Segmentation and Roof Reconstruction of Urban Buildings Based on LiDAR Point Clouds
In urban point cloud scenarios, due to the diversity of different feature types, it becomes a primary challenge to effectively obtain point clouds of building categories from urban point clouds. Therefore, this paper proposes the Enhanced Local Feature Aggregation Semantic Segmentation Network (ELFA-RandLA-Net) based on RandLA-Net, which enables ELFA-RandLA-Net to perceive local details more efficiently by learning geometric and semantic features…
POI Data Fusion Method Based on Multi-Feature Matching and Optimization
The key to geospatial data integration lies in identifying corresponding objects from different sources. Aiming at the problem of the low matching accuracy of geospatial entities under a single feature attribute, a geospatial entity matching method based on multi-feature value calculation is proposed. Firstly, when dealing with POI (point of interest) data, the similarity of POI data in terms of name, address, and distance is calculated by combin…
Airborne LiDAR Point Cloud Building Reconstruction Based on Planar Optimal Combination and Feature Line Constraints
This paper proposes a building reconstruction framework for airborne LiDAR data to address the challenge of automated modeling under conditions of uneven point cloud density and missing vertical walls, generating high-precision and structurally compact 3D building models. The method first combines adaptive resolution hypervoxels with a global graph cut optimization strategy to extract precise roof plane primitives from sparse point clouds of buil…
3D Surveying and Cultural Heritage (2 works) · Artificial Intelligence (2 works) · Automated Road and Building Extraction (2 works) · Computer Science (2 works) · Data mining (2 works) · Engineering (2 works) · Geography (2 works) · Lidar (2 works) · Mathematics (2 works) · Point cloud (2 works)