Point Cloud Approach For Modelling The Lost Volume of The Fillaboa Bridge Cutwater
Abstract
The digitization of heritage is being rapidly realised in many parts of the world, thanks to LiDAR technology. In addition to the simple digital preservation of heritage, 3D acquisition makes it possible to monitor the structural condition and assess possible damage. This paper presents a method for modelling the lost volume of a heritage bridge. The selected case study is the Fillaboa bridge in Salvaterra de Miño, Spain, which has two cutwaters with the same cutting angle, one of which is damaged and has a stone loss. The bridge was acquired with a Terrestrial Laser Scanner. The method consists of the following processes. First, the walls of the whole cutwater are segmented and aligned by the Iterative Closest Point algorithm over the damaged cutwater. Second, the distance between the two point clouds is calculated, and the damaged area is delimited in both point clouds. And third, the alpha-shape algorithm is applied to model the point cloud of the damaged area on a polygon. By searching for the optimal alpha radius, the polygon that best fits the damaged volume is generated. The proposed method also allows digital reconstruction of the damaged area, although it is sensitive to acquisition problems, which require manual interventions in the processing. The accuracy of the method is mainly dependent on the acquired point cloud registration (with an RMS error of 60mm) and the ICP registration error (31mm). Its use is limited to the existence of two geometries that allow superposition: one in good condition and one damaged to compare.
Keywords
LiDAR, Heritage, Structural Damage, Terrestrial Laser Scanning, Masonry, Reconstruction
References
- Porras-Amores C, Mazarron FR, Canas I, Villoria Saez P. Terrestial laser scanning digitalization in underground constructions. Journal of Cultural Heritage. 2019;38:213–20.
- Popovic D, Paji V, Radovi J, Govedarica M, Antoni N. Use of LiDAR technology and CityGML in the process of digitalization of cultural heritage.
- Pierdicca R, Paolanti M, Matrone F, Martini M, Morbidoni C, Malinverni ES, et al. Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritage. Vol. 12, Remote Sensing . 2020.
- Arnold E, Al-Jarrah OY, Dianati M, Fallah S, Oxtoby D, Mouzakitis A. A Survey on 3D Object Detection Methods for Autonomous Driving Applications. IEEE Transactions on Intelligent Transportation Systems. 2019;20(10):378295.
- Khanal M, Hasan M, Sterbentz N, Johnson R, Weatherly J. Accuracy Comparison of Aerial Lidar, Mobile-Terrestrial Lidar, and UAV Photogrammetric Capture Data Elevations over Different Terrain Types. Vol. 5, Infrastructures . 2020.
- Otero R, Lag, Garrido I, Arias P. Mobile indoor mapping technologies: A review. Automation in Construction. 2020;120:103399.
- Wang X, Wang Y, Ma L, Yuan P, Zhang Y. Information Processing Technology in the Digital Protection of Architectural Cultural Heritage. In: 2020 International Conference on Culture-oriented Science & Technology (ICCST). 2020. p. 4969.
- Griffiths D, Boehm J. A Review on Deep Learning Techniques for 3D Sensed Data Classification. Vol. 11, Remote Sensing . 2019.
- Malinverni ES, Pierdicca R, Paolanti M, Martini M, Morbidoni C, Matrone F, et al. Deep Learning for semantic segmentation of 3D point cloud. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019;XLII-2/W15:73542.
- Poux F, Hallot P, Neuville R, Billen R. SMART POINT CLOUD: DEFINITION AND REMAINING CHALLENGES. 2016.
- Abate D. Built-Heritage Multi-temporal Monitoring through Photogrammetry and 2D/3D Change Detection Algorithms. Studies in Conservation. 2019 Oct 3;64(7):42334.
- Lopez-Menchero Bendicho VM, Flores Gutiierrez M, Vincent ML, Grande Leon. Digital Heritage and Virtual Archaeology: An Approach Through the Framework of International Recommendations BT - Mixed Reality and Gamification for Cultural Heritage. In: Ioannides M, Magnenat-Thalmann N, Papagiannakis G, editors. Cham: Springer International Publishing; 2017. p. 326.
- Guttentag DA. Virtual reality: Applications and implications for tourism. Tourism Management. 2010;31(5):63751.
- Kan T, Buyuksalih G, Enc Ozkan G, Baskaraca P. Rapid 3d Digitalization of the Cultural Heritage: a Case Study on Istanbul Suleymaniye Social Complex (KULLIYE). ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019 May;4211:64552.
- Balado J, Diaz-Vilarino, Azenha M, Lourenco PB. Automatic Detection of Surface Damage in Round Brick Chimneys by Finite Plane Modelling from Terrestrial Laser Scanning Point Clouds. Case Study of Braganca Dukes Palace, Guimaraes, Portugal. International Journal of Architectural Heritage. 2021 May 23;115.
- Leon obles C, Reinoso-Gordo J, Gonzalez-Quinones J. Heritage Building Information Modeling (H-BIM) Applied to A Stone Bridge. ISPRS International Journal of Geo-Information. 2019 Mar 1;8(3):121.
- Franke S, Franke B, Rautenstrauch K. Strain analysis of wood components by close range photogrammetry. Materials and Structures/Materiaux et Constructions. 2007 Jan;40(1):3746.
- Arias P, Armesto J, Di-Capua D, Gonzalez-Drigo R, Lorenzo H, Perez-Gracia V. Digital photogrammetry, GPR and computational analysis of structural damages in a mediaeval bridge. Engineering Failure Analysis. 2007;14(8 SPEC. ISS.):144457.
- Sonnenberg AMC, Al-Mahaidi R. Investigation of dowel shear in RC beams using photogrammetry. Magazine of Concrete Research. 2007 Nov 25;59(9):1626.
- Pritchard D, Sperner J, Hoepner S, Tenschert R. Terrestrial laser scanning for heritage conservation: the Cologne Cathedral documentation project. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. 2017 Aug 16;IV-2/W2(2W2):21320.
- Shanoer MM, Abed FM. Evaluate 3D laser point clouds registration for cultural heritage documentation. Egyptian Journal of Remote Sensing and Space Science. 2018 Dec 1;21(3):295304.
- Olsen MJ, Asce M, Kuester F, Chang BJ, Asce SM, Hutchinson TC, et al. terrestrial Laser Scanned-Based Structural Damage Assessment. 2010;
- Soilan Sanchez-Rodriguez, Rio Barral, Perez-Collazo, Arias, Riveiro, et al. Review of Laser Scanning Technologies and Their Applications for Road and Railway Infrastructure Monitoring. Infrastructures. 2019 Sep 20;4(4):58.
- Truong-Hong L, Lindenbergh R. Extracting Bridge Components from a Laser Scanning Point Cloud. In: Lecture Notes in Civil Engineering [Internet]. Springer; 2021 [cited 2021 Jun 9]. p. 72139. Available from: https://link.springer.com/chapter/10.1007/978-3-030-51295-8_50
- Lu R, Brilakis I, Middleton CR. Detection of Structural Components in Point Clouds of Existing RC Bridges. Computer-Aided Civil and Infrastructure Engineering [Internet]. 2019 Mar [cited 2020 Feb 19];34(3):191212. Available from: http://doi.wiley.com/10.1111/mice.12407
- Walsh SB, Borello DJ, Guldur B, Hajjar JF. Data Processing of Point Clouds for Object Detection for Structural Engineering Applications. Computer-Aided Civil and Infrastructure Engineering. 2013;28(7):495508.
- Riveiro B, DeJong MJJ, Conde B. Automated processing of large point clouds for structural health monitoring of masonry arch bridges. Automation in Construction [Internet]. 2016 Dec [cited 2017 Feb 21];72:25868. Available from: http://dx.doi.org/10.1016/j.autcon.2016.02.009
- Sanchez-Rodriguez A, Riveiro B, Conde B, Soilan M. Detection of structural faults in piers of masonry arch bridges through automated processing of laser scanning data. Structural Control and Health Monitoring. 2018;25(3):114.
- Truong-Hong, L., Laefer, D. F. Laser scanning for bridge inspection. In Laser Scanning 2019; 189-214.
- Chen S, Truong-Hong L, Laefer D, Mangina E. Automated Bridge Deck Evaluation through UAV Derived Point Cloud [Internet]. CERI-ITRN2018. 2018 Aug [cited 2021 Jun 9]. Available from: http://archive.nyu.edu/handle/2451/43478
- Barrile V, Candela G, Fotia A. Point cloud segmentation using image processing techniques for structural analysis. 2019;
- He K, Gkioxari G, Dollar P, Girshick R. Mask R-CNN. Proceedings of the IEEE International Conference on Computer Vision. 2017 Feb 1;29808.
- Freiria E. Ponte de Fillaboa [Internet]. 2013 [cited 2021 May 20]. Available from: http://patrimoniogalego.net/index.php/36706/2013/03/ponte-de-fillaboa/
- Ferreira Priegue EM. Los caminos medievales de Galicia. Museo Arqueoloxico Provincial; 1988. 260.
- Aramburu-Zabala Higuera MA, Gomez Martinez M. Juan de Herrera y su influencia: actas del simposio, Camargo, 14-17 julio 1992. Ed. Universidad de Cantabria; 1993.
- Frias E, Diaz-Vilarino, Balado J, Lorenzo H. From BIM to Scan Planning and Optimization for Construction Control. Vol. 11, Remote Sensing . 2019.
- Li P, Wang R, Wang Y, Tao W. Evaluation of the ICP Algorithm in 3D Point Cloud Registration. IEEE Access. 2020;8:6803048.
- Men H, Gebre B, Pochiraju K. Color point cloud registration with 4D ICP algorithm. In: 2011 IEEE International Conference on Robotics and Automation. 2011. p. 15116.
- Xin W, Pu J. An Improved ICP Algorithm for Point Cloud Registration. In: 2010 International Conference on Computational and Information Sciences. 2010. p. 5658.
- Shi X, Liu T, Han X. Improved Iterative Closest Point(ICP) 3D point cloud registration algorithm based on point cloud filtering and adaptive fireworks for coarse registration. International Journal of Remote Sensing. 2020 Apr 17;41(8):3197220.
- Edelsbrunner H, Kirkpatrick D, Seidel R. On the shape of a set of points in the plane. IEEE Transactions on Information Theory. 1983;29(4):5519.