基于摄像头信息的三维数字孪生模型中建筑工地动态活动的重建方法

Jingyao He, Pengfei Li, Xuehui An, Chengzhi Wang
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引用次数: 0

摘要

数字孪生技术大大提高了建筑工地的管理效率;然而,动态重建工地活动却是一个相当大的挑战。本研究介绍了一种利用摄像头数据进行建筑工地活动三维重建的方法。该方法首先利用三维扫描细致地重建施工场景和动态元素,形成模型基础。它进一步整合了深度学习算法,以精确识别障碍环境中的静态和动态元素。然后应用增强型半全局块匹配算法,从图像中获取深度信息,促进精确的元素定位。最后,还引入了一种近乎实时的投影方法,该方法利用元素之间的空间关系将模型动态纳入三维基底,从而实现多视角的现场活动视图。经过模拟施工现场实验的验证,该方法的重建准确率高达 95%,令人印象深刻,这凸显了它在提高动态数字孪生模型创建效率方面的巨大潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Reconstruction Methodology of Dynamic Construction Site Activities in 3D Digital Twin Models Based on Camera Information
Digital twin technology significantly enhances construction site management efficiency; however, dynamically reconstructing site activities presents a considerable challenge. This study introduces a methodology that leverages camera data for the 3D reconstruction of construction site activities. The methodology was initiated using 3D scanning to meticulously reconstruct the construction scene and dynamic elements, forming a model base. It further integrates deep learning algorithms to precisely identify static and dynamic elements in obstructed environments. An enhanced semi-global block-matching algorithm was then applied to derive depth information from the imagery, facilitating accurate element localization. Finally, a near-real-time projection method was introduced that utilizes the spatial relationships among elements to dynamically incorporate models into a 3D base, enabling a multi-perspective view of site activities. Validated by simulated construction site experiments, this methodology showcased an impressive reconstruction accuracy reaching up to 95%, this underscores its significant potential in enhancing the efficiency of creating a dynamic digital twin model.
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