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3D modeling of Unmanned Aerial Vehicles Tilt Photogrammetry
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作者 Lingyun Li 《Journal of World Architecture》 2020年第4期10-12,共3页
Unmanned Aerial Vehicles(UAV)tilt photogrammetry technology can quickly acquire image data in a short time.This technology has been widely used in all walks of life with the rapid development in recent years especiall... Unmanned Aerial Vehicles(UAV)tilt photogrammetry technology can quickly acquire image data in a short time.This technology has been widely used in all walks of life with the rapid development in recent years especially in the rapid acquisition of high-resolution remote sensing images,because of its advantages of high efficiency,reliability,low cost and high precision.Fully using the UAV tilt photogrammetry technology,the construction image progress can be observed by stages,and the construction site can be reasonably and optimally arranged through three-dimensional modeling to create a civilized,safe and tidy construction environment. 展开更多
关键词 Unmanned aerial vehicle(UAV) tilt photogrammetry Three-dimensional modeling Multiview image dense matching Smart3D
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Optimized air-ground data fusion method for mine slope modeling
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作者 LIU Dan HUANG Man +4 位作者 TAO Zhigang HONG Chenjie WU Yuewei FAN En YANG Fei 《Journal of Mountain Science》 SCIE CSCD 2024年第6期2130-2139,共10页
Refined 3D modeling of mine slopes is pivotal for precise prediction of geological hazards.Aiming at the inadequacy of existing single modeling methods in comprehensively representing the overall and localized charact... Refined 3D modeling of mine slopes is pivotal for precise prediction of geological hazards.Aiming at the inadequacy of existing single modeling methods in comprehensively representing the overall and localized characteristics of mining slopes,this study introduces a new method that fuses model data from Unmanned aerial vehicles(UAV)tilt photogrammetry and 3D laser scanning through a data alignment algorithm based on control points.First,the mini batch K-Medoids algorithm is utilized to cluster the point cloud data from ground 3D laser scanning.Then,the elbow rule is applied to determine the optimal cluster number(K0),and the feature points are extracted.Next,the nearest neighbor point algorithm is employed to match the feature points obtained from UAV tilt photogrammetry,and the internal point coordinates are adjusted through the distanceweighted average to construct a 3D model.Finally,by integrating an engineering case study,the K0 value is determined to be 8,with a matching accuracy between the two model datasets ranging from 0.0669 to 1.0373 mm.Therefore,compared with the modeling method utilizing K-medoids clustering algorithm,the new modeling method significantly enhances the computational efficiency,the accuracy of selecting the optimal number of feature points in 3D laser scanning,and the precision of the 3D model derived from UAV tilt photogrammetry.This method provides a research foundation for constructing mine slope model. 展开更多
关键词 Air-ground data fusion method Mini batch K-Medoids algorithm Ebow rule Optimal cluster number 3D laser scanning UAV tilt photogrammetry
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