Computer vision-based construction progress monitoring

被引:55
|
作者
Reja, Varun Kumar [1 ,2 ]
Varghese, Koshy [1 ]
Ha, Quang Phuc [2 ]
机构
[1] IIT Madras, BTCM Div, Dept Civil Engn, Chennai, India
[2] Univ Technol Sydney, Fac Engn & IT, Sydney, NSW 2007, Australia
关键词
Progress monitoring; Computer vision; Automated construction; Data acquisition; 3D reconstruction; As-built modelling; Point cloud; Scan to BIM; Literature review; Digital Twin; 3D BUILDING MODELS; SCAN-TO-BIM; POINT CLOUDS; RECONSTRUCTION; REGISTRATION; RECOGNITION; EXTRACTION; GENERATION; KNOWLEDGE; TRACKING;
D O I
10.1016/j.autcon.2022.104245
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Automating the process of construction progress monitoring through computer vision can enable effective control of projects. Systematic classification of available methods and technologies is necessary to structure this complex, multi-stage process. Using the PRISMA framework, relevant studies in the area were identified. The various concepts, tools, technologies, and algorithms reported by these studies were iteratively categorised, developing an integrated process framework for Computer-Vision-Based Construction Progress Monitoring (CVCPM). This framework comprises: data acquisition and 3D-reconstruction, as-built modelling, and progress assessment. Each stage is discussed in detail, positioning key studies, and concurrently comparing the methods used therein. The four levels of progress monitoring are defined and found to strongly influence all stages of the framework. The need for benchmarking CV-CPM pipelines and components are discussed, and potential research questions within each stage are identified. The relevance of CV-CPM to support emerging areas such as Digital Twin is also discussed.
引用
收藏
页数:17
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