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J.Y. Kang, J.S. Park, H.S. Park, "Reinforcing Bar Segmentation from Depth-Camera-Captured Point Cloud Data", in P. Iványi, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Twelfth International Conference on Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 8, Paper 7.1, 2024, doi:10.4203/ccc.8.7.1

Keywords: rebar inspection, rebar, depth-camera, point cloud data, segmentation, normal vector.

Abstract

Reinforced concrete, a composite material composed of concrete and rebars, is one of the most widely used materials in buildings. Rebar inspection at construction sites is recommended to mitigate potential risks associated with the omission or improper installation of rebars. However, current rebar inspection conducted on-site is predominantly manual, which is time consuming and labor-intensive. In this study, a new method is proposed to segment the rebar-related point cloud data from depth-camera-captured point cloud data. This method utilizes the normal vectors of tangent planes at each point to segment the rebar-related portions leveraging the directional differences between rebar and floor-related points for effective segmentation. To validate this method, experiments were conducted with six 1.2 m rebars under various experimental conditions. The accuracy of segmentation was assessed by comparing the actual spacing between the rebars and the distances between the segmented rebar points. The results demonstrated that the proposed method can effectively segment rebars and accurately measure the interval instances.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 8 PROCEEDINGS OF THE TWELFTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY Edited by: P. Iványi, J. Kruis and B.H.V. Topping Paper 7.1 Reinforcing Bar Segmentation from Depth-Camera-Captured Point Cloud Data J.Y. Kang, J.S. Park and H.S. Park Architectural Engineering, Yonsei University, Republie of South Korea doi:10.4203/ccc.8.7.1 Full Bibliographic Reference for this paper J.Y. Kang, J.S. Park, H.S. Park, "Reinforcing Bar Segmentation from Depth-Camera-Captured Point Cloud Data", in P. Iványi, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Twelfth International Conference on Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 8, Paper 7.1, 2024, doi:10.4203/ccc.8.7.1 Keywords: rebar inspection, rebar, depth-camera, point cloud data, segmentation, normal vector. Abstract Reinforced concrete, a composite material composed of concrete and rebars, is one of the most widely used materials in buildings. Rebar inspection at construction sites is recommended to mitigate potential risks associated with the omission or improper installation of rebars. However, current rebar inspection conducted on-site is predominantly manual, which is time consuming and labor-intensive. In this study, a new method is proposed to segment the rebar-related point cloud data from depth-camera-captured point cloud data. This method utilizes the normal vectors of tangent planes at each point to segment the rebar-related portions leveraging the directional differences between rebar and floor-related points for effective segmentation. To validate this method, experiments were conducted with six 1.2 m rebars under various experimental conditions. The accuracy of segmentation was assessed by comparing the actual spacing between the rebars and the distances between the segmented rebar points. The results demonstrated that the proposed method can effectively segment rebars and accurately measure the interval instances. download the full-text of this paper (PDF, 8 pages, 1023 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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