Shape recognition with point clouds in rebars

Kosei Ishida, Naruo Kano, Kenji Kimoto

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Purpose: In this paper, the authors describe the methods of inspecting the quality of reinforced concrete structure using point-clouds data acquired from a 3D-laser scanner. A 3D-laser scanner is an outstanding device to analyze a realworld object and to collect digital data on its shape. Inspections of the quality of reinforced concrete structure using point clouds are required for novel methods which count the quantity of rebar material and to check the space of each rebar. Method: To inspect with the use of 3Dpoint clouds, we developed a method of 3D-point-clouds recognition of the rebars elements. In this paper the authors show three methods to analyze point clouds collected in rebars of building structures. Firstly, the authors developed a method of noise reduction to make a clear distinction between object surface points and noise points; this is important because point clouds in rebars have much noise that can disturb subsequent analysis. Secondly, the authors developed a method of abstracting point clouds on reinforcement bars. Thirdly, the authors developed a method dividing point clouds on reinforcement bars into hoops and wall horizontal reinforcement bars. The authors scanned reinforced bars of columns and walls at a construction site of an apartment and then applied the three methods to analyze the point clouds data. Results & Discussion: In this experiment, our methods were able to identify 3D point clouds as main bars, horizontal bars, and hoops. We were able to measure the object from 3D-point-clouds data at any time as well as being able to develop an automatic inspection system.

    Original languageEnglish
    Title of host publication2012 Proceedings of the 29th International Symposium of Automation and Robotics in Construction, ISARC 2012
    Publication statusPublished - 2012
    Event29th International Symposium of Automation and Robotics in Construction, ISARC 2012 - Eindhoven
    Duration: 2012 Jun 262012 Jun 29

    Other

    Other29th International Symposium of Automation and Robotics in Construction, ISARC 2012
    CityEindhoven
    Period12/6/2612/6/29

    Fingerprint

    Shape Recognition
    Point Cloud
    Reinforcement
    Concrete construction
    Reinforced concrete
    Inspection
    Laser Scanner
    Concrete Structures
    Reinforced Concrete
    Lasers
    Noise abatement
    Horizontal
    Noise Reduction
    Count

    Keywords

    • 3D laser scanner
    • 3DCAD
    • Point cloud
    • Quality control
    • Reinforcement work

    ASJC Scopus subject areas

    • Civil and Structural Engineering
    • Building and Construction
    • Modelling and Simulation

    Cite this

    Ishida, K., Kano, N., & Kimoto, K. (2012). Shape recognition with point clouds in rebars. In 2012 Proceedings of the 29th International Symposium of Automation and Robotics in Construction, ISARC 2012

    Shape recognition with point clouds in rebars. / Ishida, Kosei; Kano, Naruo; Kimoto, Kenji.

    2012 Proceedings of the 29th International Symposium of Automation and Robotics in Construction, ISARC 2012. 2012.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Ishida, K, Kano, N & Kimoto, K 2012, Shape recognition with point clouds in rebars. in 2012 Proceedings of the 29th International Symposium of Automation and Robotics in Construction, ISARC 2012. 29th International Symposium of Automation and Robotics in Construction, ISARC 2012, Eindhoven, 12/6/26.
    Ishida K, Kano N, Kimoto K. Shape recognition with point clouds in rebars. In 2012 Proceedings of the 29th International Symposium of Automation and Robotics in Construction, ISARC 2012. 2012
    Ishida, Kosei ; Kano, Naruo ; Kimoto, Kenji. / Shape recognition with point clouds in rebars. 2012 Proceedings of the 29th International Symposium of Automation and Robotics in Construction, ISARC 2012. 2012.
    @inproceedings{6533ed934030475eb993f5efae4d32d2,
    title = "Shape recognition with point clouds in rebars",
    abstract = "Purpose: In this paper, the authors describe the methods of inspecting the quality of reinforced concrete structure using point-clouds data acquired from a 3D-laser scanner. A 3D-laser scanner is an outstanding device to analyze a realworld object and to collect digital data on its shape. Inspections of the quality of reinforced concrete structure using point clouds are required for novel methods which count the quantity of rebar material and to check the space of each rebar. Method: To inspect with the use of 3Dpoint clouds, we developed a method of 3D-point-clouds recognition of the rebars elements. In this paper the authors show three methods to analyze point clouds collected in rebars of building structures. Firstly, the authors developed a method of noise reduction to make a clear distinction between object surface points and noise points; this is important because point clouds in rebars have much noise that can disturb subsequent analysis. Secondly, the authors developed a method of abstracting point clouds on reinforcement bars. Thirdly, the authors developed a method dividing point clouds on reinforcement bars into hoops and wall horizontal reinforcement bars. The authors scanned reinforced bars of columns and walls at a construction site of an apartment and then applied the three methods to analyze the point clouds data. Results & Discussion: In this experiment, our methods were able to identify 3D point clouds as main bars, horizontal bars, and hoops. We were able to measure the object from 3D-point-clouds data at any time as well as being able to develop an automatic inspection system.",
    keywords = "3D laser scanner, 3DCAD, Point cloud, Quality control, Reinforcement work",
    author = "Kosei Ishida and Naruo Kano and Kenji Kimoto",
    year = "2012",
    language = "English",
    booktitle = "2012 Proceedings of the 29th International Symposium of Automation and Robotics in Construction, ISARC 2012",

    }

    TY - GEN

    T1 - Shape recognition with point clouds in rebars

    AU - Ishida, Kosei

    AU - Kano, Naruo

    AU - Kimoto, Kenji

    PY - 2012

    Y1 - 2012

    N2 - Purpose: In this paper, the authors describe the methods of inspecting the quality of reinforced concrete structure using point-clouds data acquired from a 3D-laser scanner. A 3D-laser scanner is an outstanding device to analyze a realworld object and to collect digital data on its shape. Inspections of the quality of reinforced concrete structure using point clouds are required for novel methods which count the quantity of rebar material and to check the space of each rebar. Method: To inspect with the use of 3Dpoint clouds, we developed a method of 3D-point-clouds recognition of the rebars elements. In this paper the authors show three methods to analyze point clouds collected in rebars of building structures. Firstly, the authors developed a method of noise reduction to make a clear distinction between object surface points and noise points; this is important because point clouds in rebars have much noise that can disturb subsequent analysis. Secondly, the authors developed a method of abstracting point clouds on reinforcement bars. Thirdly, the authors developed a method dividing point clouds on reinforcement bars into hoops and wall horizontal reinforcement bars. The authors scanned reinforced bars of columns and walls at a construction site of an apartment and then applied the three methods to analyze the point clouds data. Results & Discussion: In this experiment, our methods were able to identify 3D point clouds as main bars, horizontal bars, and hoops. We were able to measure the object from 3D-point-clouds data at any time as well as being able to develop an automatic inspection system.

    AB - Purpose: In this paper, the authors describe the methods of inspecting the quality of reinforced concrete structure using point-clouds data acquired from a 3D-laser scanner. A 3D-laser scanner is an outstanding device to analyze a realworld object and to collect digital data on its shape. Inspections of the quality of reinforced concrete structure using point clouds are required for novel methods which count the quantity of rebar material and to check the space of each rebar. Method: To inspect with the use of 3Dpoint clouds, we developed a method of 3D-point-clouds recognition of the rebars elements. In this paper the authors show three methods to analyze point clouds collected in rebars of building structures. Firstly, the authors developed a method of noise reduction to make a clear distinction between object surface points and noise points; this is important because point clouds in rebars have much noise that can disturb subsequent analysis. Secondly, the authors developed a method of abstracting point clouds on reinforcement bars. Thirdly, the authors developed a method dividing point clouds on reinforcement bars into hoops and wall horizontal reinforcement bars. The authors scanned reinforced bars of columns and walls at a construction site of an apartment and then applied the three methods to analyze the point clouds data. Results & Discussion: In this experiment, our methods were able to identify 3D point clouds as main bars, horizontal bars, and hoops. We were able to measure the object from 3D-point-clouds data at any time as well as being able to develop an automatic inspection system.

    KW - 3D laser scanner

    KW - 3DCAD

    KW - Point cloud

    KW - Quality control

    KW - Reinforcement work

    UR - http://www.scopus.com/inward/record.url?scp=84893249740&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84893249740&partnerID=8YFLogxK

    M3 - Conference contribution

    AN - SCOPUS:84893249740

    BT - 2012 Proceedings of the 29th International Symposium of Automation and Robotics in Construction, ISARC 2012

    ER -