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《Geomatics World》 2017-04
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Point Cloud Auto-classification Based on UAV Sensor Data and Word Bag Model

JIANG Jiong;WANG Congmin;HE Yutao;LI Tianxiang;XU Jie;Ningbo Power Supply Company of State Grid Zhejiang Electric Power Company;  
Point cloud classification is a key step in Li DAR data application and an important research topic.Aiming at the problem of low recognition rate of Li DAR point cloud data,this paper presents a method of classification of airborne Li DAR point cloud data based on word bag model with voxel point cloud as the research object.Considering the lack of texture information in point cloud data,this paper analyzes the characteristics of point cloud data and image data synthetically,and extracts the geometric features and image feature classification characteristics of point cloud.Then the cloud data is divided in voxel and the phonetic model of the scene information is constructed based on the voxel.Finally,the classification of the scene is completed based on the random classification classifier.The Vaihingen data provided by ISPRS are used as experimental data.The experimental results show that the proposed model can be effectively improved the classification quality of point cloud,and the classification rate can get more than 93%.
【Fund】: 国网浙江省电力公司2016年度重大科技研究项目(5211NB15014U)资助
【CateGory Index】: P237
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