Indoor and outdoor multi-source 3D data fusion method for ancient buildings

IF 0.6 Q4 ENGINEERING, MECHANICAL Journal of Measurements in Engineering Pub Date : 2022-09-26 DOI:10.21595/jme.2022.22710
Shuangfeng Wei, Changchang Liu, Nian Tang, Xiaoyu Zhao, Haocheng Zhang, Xiaohang Zhou
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引用次数: 1

Abstract

Ancient buildings carry important information, such as ancient politics, economy, culture, customs. However, with the course of time, ancient buildings are often damaged to different degrees, so the restoration of ancient buildings is of great importance from the historical point of view. There are three commonly used non-contact measurement methods, including UAV-based oblique photogrammetry, terrestrial laser scanning, and close-range photogrammetry. These methods can provide integrated three-dimensional surveys of open spaces, indoor and outdoor surfaces for ancient buildings. Theoretically, the combined use of the three measurement methods can provide 3D (three-dimensional) data support for the protection and repair of ancient buildings. However, data from the three methods need to be fused urgently, because if the image data is not used, it will lead to a lack of real and intuitive texture information, and if only image matching point clouds are used, their accuracy will be lower than that of terrestrial laser scanning point clouds, and it will also lead to a lack of digital expression for components with high indoor historical value of ancient buildings. Therefore, in this paper, a data fusion method is proposed to achieve multi-source and multi-scale 3D data fusion of indoor and outdoor surfaces. It takes the terrestrial laser point cloud as the core, and based on fine component texture features and building outline features, respectively, the ground close-range image matching point cloud and UAV oblique image matching point cloud are registered with the terrestrial laser point cloud. This method unifies the data from three measurements in the point cloud and realizes the high-precision fusion of these three data. Based on the indoor and outdoor 3D full-element point cloud formed by the proposed method, it will constitute a visual point cloud model in producing plans, elevations, sections, orthophotos, and other elements for the study of ancient buildings.
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古建筑室内外多源三维数据融合方法
古建筑承载着古代政治、经济、文化、风俗等重要信息。然而,随着时间的推移,古建筑往往会受到不同程度的破坏,因此从历史的角度来看,古建筑的修复具有重要意义。常用的非接触测量方法有三种,包括基于无人机的倾斜摄影测量、地面激光扫描和近距离摄影测量。这些方法可以为古建筑提供开放空间、室内外表面的综合三维测量。理论上,三种测量方法的结合使用可以为古建筑的保护和修复提供3D(三维)数据支持。然而,这三种方法的数据急需融合,因为如果不使用图像数据,将导致缺乏真实直观的纹理信息,如果只使用图像匹配点云,其精度将低于地面激光扫描点云,同时也会导致古建筑室内历史价值较高的构件缺乏数字化表达。因此,本文提出了一种数据融合方法,实现室内外表面多源、多尺度三维数据融合。它以地面激光点云为核心,分别基于精细组件纹理特征和建筑物轮廓特征,将地面近距离图像匹配点云和无人机倾斜图像匹配点云和地面激光点云中进行配准。该方法将三次测量的数据统一在点云中,实现了三次测量数据的高精度融合。基于所提出的方法形成的室内外三维全要素点云,它将在生成平面图、立面图、剖面图、正射影像等要素时构成一个视觉点云模型,用于古建筑研究。
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来源期刊
Journal of Measurements in Engineering
Journal of Measurements in Engineering ENGINEERING, MECHANICAL-
CiteScore
2.00
自引率
6.20%
发文量
16
审稿时长
16 weeks
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