河南城建学院学报2026，Vol.35Issue(1)：55-60,86,7.DOI:10.14140/j.cnki.hncjxb.2026.01.008
基于建筑轮廓特征的建筑景观模型简化研究
Research on simplifying architectural landscape models based on architectural contour features
摘要
Abstract
Traditional simplification methods often overlook the architectural contour features,resulting in the loss of aesthetic and cultural attributes of the model.A simplified method for architectural landscape models that balances visual authenticity and computational efficiency is proposed,focusing on the Huizhou ancient architectural complex and the Lujiazui high-rise architectural complex.By using the minimum bounding ball algorithm to extract the outer contour of buildings,combined with viewpoint driven hierarchi-cal detail model construction technology,a multi-scale model is dynamically generated to balance data vol-ume and visual quality.Based on the drone oblique photography point cloud and BIM model data,the con-tour fitting error rate is used as a quantitative indicator to verify the reliability of the data.The results show that the proposed method takes 17.8 seconds to complete the extraction of a four-level hierarchical detail model at 5 000 observation points,and the quality of contour extraction reaches 50.67%,which is about 20%more efficient than the comparative method.Urban and rural application scenarios are divided into cul-tural heritage and smart city.Among them,the direction of cultural heritage focuses on traditional villages in Huizhou,and the direction of smart city focuses on the central urban area of Shanghai,which verifies that the algorithm can effectively preserve the architectural contour features and achieve efficient rendering,pro-viding a technical path for real-time visualization of smart cities and high fidelity digitization of cultural heri-tage in the context of urban and rural differentiation.关键词
建筑轮廓/景观特征/三维模型/模型简化Key words
architectural contour/landscape features/3D model/model simplification分类
建筑与水利引用本文复制引用
李娜,张策..基于建筑轮廓特征的建筑景观模型简化研究[J].河南城建学院学报,2026,35(1):55-60,86,7.基金项目
安徽省教育厅自然科学研究重点项目(2023AH052149) （2023AH052149）
