Efficient and lightweight 3D building reconstruction from drone imagery using sparse line and point clouds  

作　　者：Xiongjie YIN Jinquan HE Zhanglin CHENG 

机构地区：[1]College of Mechanical and Control Engineering,Guilin University of Technology,Guilin 541006,China [2]Shenzhen VisuCA Key Lab,Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,China

出　　处：《虚拟现实与智能硬件(中英文)》2025年第2期111-126,共16页Virtual Reality & Intelligent Hardware

基　　金：Supported by the Guangdong Major Project of Basic and Applied Basic Research(2023B0303000016),and the National Natural Science Foundation of China(U21A20515).

摘　　要：Efficient three-dimensional(3D)building reconstruction from drone imagery often faces data acquisition,storage,and computational challenges because of its reliance on dense point clouds.In this study,we introduced a novel method for efficient and lightweight 3D building reconstruction from drone imagery using line clouds and sparse point clouds.Our approach eliminates the need to generate dense point clouds,and thus significantly reduces the computational burden by reconstructing 3D models directly from sparse data.We addressed the limitations of line clouds for plane detection and reconstruction by using a new algorithm.This algorithm projects 3D line clouds onto a 2D plane,clusters the projections to identify potential planes,and refines them using sparse point clouds to ensure an accurate and efficient model reconstruction.Extensive qualitative and quantitative experiments demonstrated the effectiveness of our method,demonstrating its superiority over existing techniques in terms of simplicity and efficiency.

关 键 词：3D reconstruction Line clouds Sparse clouds Lightweight models 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]