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莫民静

（广西工业职业技术学院 建筑工程学院 ，广西 南宁 530001)

摘   要： 针对易受噪声数据、建筑物复杂程度干扰，高层建筑边缘空间规划模型的重建完整率 、正确率低 的问题，提出高层建筑边缘空间 BIM 透视式增强现实重建模型 。采用MVS 点云算法，采集高层建筑边缘空间的点云集合，剔除集合中的噪声 ，采取 BIM 技术 ，提取高层建筑边缘空间的轮廓特征，将轮廓特征分割成长方体 与三角体，采用投影映射，匹配轮廓的三维角点坐标，引入纹理映射法，优化高层建筑边缘空间 BIM 透视式纹理，完成高层建筑边缘空间重建 。实验结果表明，所提方法的重建效果好，重建完整率高 、正确率高 ，重建几何精度较高。

关键词： 点云集合； 统计滤波； 位置判断函数； 轮廓透视投影； 相对深度； 纹理映射

中图分类号： TN911. 73      

文献标志码： A      

文章编号： 1005-8249 (2023) 05-0133-07

DOI : 10. 19860/j.cnki.issn1005-8249.2023.05.021

MO Minjing

( School of Architectural Engineering , Guangxi Vocational & Technical Institute of Industry ,

Nanning 530001 , China)

Abstract: Aiming at the problems of being easily disturbed by noise data and building complexity, and the low reconstruction integrity and accuracy of high-rise building edge space planning model, a BIM perspective augmented reality reconstruction model of high-rise building edge space is proposed. MVS point cloud algorithm is adopted to collect the point cloud set of high-rise building edge space, eliminate the noise in the set, and BIM Technology is adopted to extract the contour features of high-rise building edge space. The contour features are divided into cuboids and triangles. Projection mapping is adopted to match the three-dimensional corner coordinates of the contour, and texture mapping method is introduced to optimize the BIM perspective texture of high-rise building edge space to complete the reconstruction of high-rise building edge space. Experimental results show that the proposed method has good reconstruction effect, high reconstruction integrity rate, high accuracy and high geometric accuracy.

Keywords: BP neural network model; statistical filtering; location judgment function; contour perspective projection; relative depth;texture mapping

∗基金项目： 广西工业职业技术学院科学研究重点课题“ EPC+ BIM+装配式 ” 新型建造模式的应用研究（ 桂工业院科研 Y2021 KY001 ) ; 2022 年度广西 高 校中 青 年 教 师 科 研 基 础 能 力 提 升 项 目 “ EPC + BIM + 装 配 式 ” 新 型 建 造 模 式 的 应 用 研 究 (2022KY1289) 。

 作者简介： 莫民静  (1987—) , 女 ，壮族 ，本科 ，讲师 ，主要研究方向： 土木工程 ，BIM 技术。

 收稿日期： 2022-07-28