Accuracy Evaluation of 3D Geometry from Low-Attitude UAV Images: A Case Study at Zijin Mine
This study investigates the usability of low-attitude unmanned aerial vehicle (UAV) acquiring high resolution images for the geometry reconstruction of opencast mine.Image modelling techniques like Structure from Motion (SfM) and Patch-based Multiview Stereo (PMVS) algorithms are used to generate dense 3D point cloud from UAV collections.Then,precision of 3D point cloud will be first evaluated based on Real-time Kinematic (RTK) ground control points (GCPs) at point level.The experimental result shows that the mean square error of the UAV point cloud is 0.11m.Digital surface model (DSM) of the study area is generated from UAV point cloud,and compared with that from the Terrestrial Laser Scanner (TLS) data for further comparison at the surface level.Discrepancy map of 3D distances based on DSMs shows that most deviation is less than ±0.4m and the relative error of the volume is 1.55%.
UAV 3D Geometry Opencast Mine Structure from Motion (SfM) Accuracy Evaluation
Qiuling Wang Lixin Wu Shaojie Chen Defu Shu Zhihua Xu Fashuai Li Ran Wang
Key Laboratory of Environmental Change & Natural Disaster of MOE,Beijing Normal University,Beijing 1 IOT Perception Mine Research Centre,China University of Mining and Technology,Xuzhou 221008,China Resources Department,Longyan College,Longyan 364000,China Zijin MiningGroup Co.,Ltd,Shanghang 364200.China College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing
国内会议
苏州
英文
297-300
2014-05-14（万方平台首次上网日期，不代表论文的发表时间）