Proceedings of the 2021 European Conference on Computing in Construction
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Efficient Vertical Object Detection in Large High-Quality Point Clouds of Construction Sites
Miguel Vega 1, Alexander Braun 1, Heiko Bauer 2, Florian Noichl 1, André Borrmann 11 Chair of Computational Modeling and Simulation, Technical University of Munich, Germany
2 FARO EUROPE GmbH & Co.KG., Korntal-Münchingen, GermanyDOI: 10.35490/EC3.2021.156Abstract: Even when adherence to the project schedule is a critical performance metric, still 53% of construction projects exhibit schedule delays. To contribute to efficient construction progress monitoring, a method is proposed to detect temporary objects in scans of construction sites. The proposed workflow includes: image processing, computer vision, and deep learning techniques. The method was tested on three real scans and with three object categories (cranes, scaffolds, and formwork). It achieved average rates above 88% for precision and recall and outstanding computational performance (1s to process 10^5points). These metrics demonstrate the method’s capability to segment point clouds of construction sites. Keywords: workflow, process patterns, protocols, documentation, blockchainPages: 148 - 157 Paper:EC32021_156