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莫民靜

（廣西工業職業技術學院 建筑工程學院 ，廣西 南寧 530001)

摘   要： 針對易受噪聲數據、建筑物復雜程度干擾，高層建筑邊緣空間規劃模型的重建完整率 、正確率低 的問題，提出高層建筑邊緣空間 BIM 透視式增強現實重建模型 。采用MVS 點云算法，采集高層建筑邊緣空間的點云集合，剔除集合中的噪聲 ，采取 BIM 技術 ，提取高層建筑邊緣空間的輪廓特征，將輪廓特征分割成長方體 與三角體，采用投影映射，匹配輪廓的三維角點坐標，引入紋理映射法，優化高層建筑邊緣空間 BIM 透視式紋理，完成高層建筑邊緣空間重建 。實驗結果表明，所提方法的重建效果好，重建完整率高 、正確率高 ，重建幾何精度較高。

關鍵詞： 點云集合； 統計濾波； 位置判斷函數； 輪廓透視投影； 相對深度； 紋理映射

中圖分類號： TN911. 73      

文獻標志碼： A      

文章編號： 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

?基金項目： 廣西工業職業技術學院科學研究重點課題“ EPC+ BIM+裝配式 ” 新型建造模式的應用研究（ 桂工業院科研 Y2021 KY001 ) ; 2022 年度廣西 高 校中 青 年 教 師 科 研 基 礎 能 力 提 升 項 目 “ EPC + BIM + 裝 配 式 ” 新 型 建 造 模 式 的 應 用 研 究 (2022KY1289) 。

 作者簡介： 莫民靜  (1987—) , 女 ，壯族 ，本科 ，講師 ，主要研究方向： 土木工程 ，BIM 技術。

 收稿日期： 2022-07-28