A Classification Method for Mobile Laser Scanning Data Based on Object Feature Extraction
LI Ting1,2, ZHAN Qing-ming1,2,3, YU Liang2,3
1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
2. Research Centre for Digital City, Wuhan University, Wuhan 430072, China;
3. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan 430074, China
Abstract:Compared with traditional survey technologies, mobile laser scanning has many advantages. Its characteristics make it possible to rapidly acquire large-area high-precision 3D spatial data for reconstruction of 3D (three-dimensional) model. This paper focuses on the classification of mobile laser scanning data. The authors present a multi-level classification method based on object feature extraction, namely extraction of main features by PCA(Principal Component Analysis). This method was applied to blocks point data obtained by mobile laser scanning, and the results show that the proposed classification method is promising.
李婷, 詹庆明, 喻亮. 基于地物特征提取的车载激光点云数据分类方法[J]. 国土资源遥感, 2012, 24(1): 17-21.
LI Ting, ZHAN Qing-ming, YU Liang. A Classification Method for Mobile Laser Scanning Data Based on Object Feature Extraction. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(1): 17-21.
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