Jianxiong Zhang , Hongxing Qiu , Yunlong Lu , Jian Sun , Guanqi Lan
{"title":"3D reconstruction and dimension recovery algorithm for architectural structures using sequential images and photography trajectories","authors":"Jianxiong Zhang , Hongxing Qiu , Yunlong Lu , Jian Sun , Guanqi Lan","doi":"10.1016/j.autcon.2025.106465","DOIUrl":null,"url":null,"abstract":"<div><div>Accurate 3D reconstruction and dimension recovery of engineering structures are crucial for dimensional inspection, whereas classic SfM + MVS reconstruction only generates scaled similar models. To address this issue, a 3D reconstruction and dimension recovery algorithm using sequential images and photography trajectories is proposed. The algorithm improves traditional 3D reconstruction by integrating inertial measurement unit (IMU) data to estimate photography trajectories, down-sampling and time-aligning trajectory points using timestamps of sequential images as reference, and solving the scale factor via data fusion to recover absolute dimensions. Laboratory validation on specimens shows that the proposed algorithm achieves a 0.58 % mean relative error (MRE) between calculated and measured dimensions, confirming high accuracy; further validation on practical structures demonstrates that, paired with the smart terminal-based mobile scheme, the proposed algorithm yields 1.29 % MRE for small-scale components and 2.73 % for large-scale structures, further verifying the engineering practicability.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"179 ","pages":"Article 106465"},"PeriodicalIF":11.5000,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation in Construction","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0926580525005059","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Accurate 3D reconstruction and dimension recovery of engineering structures are crucial for dimensional inspection, whereas classic SfM + MVS reconstruction only generates scaled similar models. To address this issue, a 3D reconstruction and dimension recovery algorithm using sequential images and photography trajectories is proposed. The algorithm improves traditional 3D reconstruction by integrating inertial measurement unit (IMU) data to estimate photography trajectories, down-sampling and time-aligning trajectory points using timestamps of sequential images as reference, and solving the scale factor via data fusion to recover absolute dimensions. Laboratory validation on specimens shows that the proposed algorithm achieves a 0.58 % mean relative error (MRE) between calculated and measured dimensions, confirming high accuracy; further validation on practical structures demonstrates that, paired with the smart terminal-based mobile scheme, the proposed algorithm yields 1.29 % MRE for small-scale components and 2.73 % for large-scale structures, further verifying the engineering practicability.
期刊介绍:
Automation in Construction is an international journal that focuses on publishing original research papers related to the use of Information Technologies in various aspects of the construction industry. The journal covers topics such as design, engineering, construction technologies, and the maintenance and management of constructed facilities.
The scope of Automation in Construction is extensive and covers all stages of the construction life cycle. This includes initial planning and design, construction of the facility, operation and maintenance, as well as the eventual dismantling and recycling of buildings and engineering structures.