Work

Safety Helmet-Based Scale Recovery for Low-Cost Monocular 3D Reconstruction on Construction Sites

Year: 2025

Type: article

Abstract: Three-dimensional (3D) reconstruction is increasingly being adopted in construction site management. While most existing studies rely on auxiliary equipment such as LiDAR and depth cameras, monocular depth estimation offers broader applicability under typical site conditions, yet it has received limited attention due to the inherent scale ambiguity in monocular vision. To address this limitation, this study proposes a safety helmet-based scale recovery framework that enables low-cost, monocular 3D reconstruction for construction site monitoring. The method utilizes safety helmets as exemplary scale carriers due to their standardized dimensions and frequent appearance in construction scenes. A Standard Template Library (STL) comprising multi-angle safety helmet masks and dimensional information is established and linked to site imagery through template matching. Following three-dimensional scale recovery, multi-frame fusion is applied to optimize the scale factors. Experimental results on multiple real construction videos demonstrate that the proposed method achieves high reconstruction accuracy, with a mean relative error below 10% and outliers not exceeding 5%, across diverse construction environments without site-specific calibration. This work aims to contribute to the practical application of monocular vision in engineering management by leveraging ubiquitous site objects as metrological references.

Source: Buildings

DOI: 10.3390/buildings15234291

Authors: Jianyu Ren, Lingling Wang, Xuanxuan Liu, Linghong Zeng

Institutions: Hunan University, State Grid Hunan Electric Power Company Limited

Language: English

Topic: Advanced Vision and Imaging

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $3,137