基于三维智能图像分析的混凝土结构装配技术

Limei Cao, Xiao Song
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引用次数: 0

摘要

目前,构件安装临时连接尚无标准做法。如何使构件临时连接更加高效、准确,是混凝土预制装配式建筑现浇连接部位施工的关键。为了改进混凝土结构的装配技术,本文结合三维智能图像分析技术进行仿真,分析比较了几种常用的电子图像稳定算法,详细论述了基于灰色投影法的视频图像稳定技术,并给出了实验结果。此外,本文还分析比较了常见的移动目标跟踪算法,如基于特征的跟踪、基于区域匹配的跟踪、基于动态轮廓的跟踪和基于三维模型的跟踪等。此外,本文还研究了基于 Camshift 算法的目标跟踪算法,并在该算法的支持下构建了智能混凝土结构的装配模型。通过实验验证可知,基于三维智能图像分析的混凝土结构装配模型在实验评价中的性能分布介于[81,89]之间,实验研究表明,基于三维智能图像分析的混凝土结构装配模型能有效提高混凝土结构的装配效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Concrete structure assembly technology based on 3D intelligent image analysis

At present, there is no standard practice for temporary connection of component installation. How to make temporary connections to components more efficient and accurate is the key to the construction of cast-in-place connection parts in concrete prefabricated buildings. In order to improve the assembly technology of concrete structures, this paper combines three-dimensional intelligent image analysis technology for simulation, analyzes and compares several common electronic image stabilization algorithms, discusses the video image stabilization technology based on gray projection method in detail, and gives experimental results. Moreover, this paper analyzes and compares common moving target tracking algorithms, such as feature-based tracking, region matching-based tracking, dynamic contour-based tracking, and 3D model-based tracking. In addition, this paper studies the target tracking algorithm based on the Camshift algorithm, and constructs the assembly model of the intelligent concrete structure with the support of the algorithm. Through experimental verification, it is known that the performance distribution of the concrete structure assembly model based on 3D intelligent image analysis in experimental evaluation is between [81, 89], the experimental study shows that the concrete structure assembly model based on 3D intelligent image analysis can effectively improve the assembly effect of concrete structure.

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