The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
SVM-Based Classification of Segmented Airborne LiDAR Point Clouds in Urban Areas
Open accessAbstract
Object-based point cloud analysis (OBPA) is useful for information extraction from airborne LiDAR point clouds. An object-based classification method is proposed for classifying the airborne LiDAR point clouds in urban areas herein. In the process of classification, the surface growing algorithm is employed to make clustering of the point clouds without outliers, thirteen features of the geometry, radiometry, topology and echo characteristics are calculated, a support vector machine (SVM) is utilized to classify the segments, and connected component analysis for 3D point clouds is proposed to optimize the original classification results. Three datasets with different point densities and complexities are employed to test our method. Experiments suggest that the proposed method is capable of making a classification of the urban point clouds with the overall classification accuracy larger than 92.34% and the Kappa coefficient larger than 0.8638, and the classification accuracy is promoted with the increasing of the point density, which is meaningful for various types of applications.
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Perception, Planning, Control, and Coordination for Autonomous Vehicles
Pendleton, S., Andersen, H., Du, X., Shen, X., Meghjani, M., Eng, Y., Rus, D., & Ang, M. (2017) · Machines · doi:10.3390/machines5010006 · Cited by 657
Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation
Xie, Y., Tian, J., & Zhu, X. X. (2020) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2019.2937630 · Cited by 482
Metadata
- Authors
- Zhang, J., Lin, X., & Ning, X.
- Venue
- Remote Sensing
- Publisher
- MDPI AG
- Published
- 2013-07-31
- Volume
- 5
- Issue
- 8
- Pages
- 3749-3775
- ISSN
- 2072-4292 (ISSN-L)
- OpenAlex
- W1994699846
- Cited by
- 274
- References
- 19
- FWCI
- 7.63
- Type
- journal article
- Language
- en
- Open access
- gold
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