Using targets in fieldwork with TLS and its implications on the coarse registration

Authors

DOI:

https://doi.org/10.5377/arquitectura.v10i20.21775

Keywords:

Heritage, laser-Scanner, point-cloud, register, target

Abstract

In point cloud processing, registration is the activity of joining a pair of these complementary models. This is done by identifying at least three common points in a pair of point clouds. In this regard, there are some controversies associated with the use of targets, which are instruments designed to facilitate the point cloud joining process in the office (post-processing). This research sought to determine the difference in point cloud registration by contrasting the target-based point method (using targets) and the natural environment point-based method (without the use of targets). For this, five participants processed four datasets: two with the use of targets and two without the use of targets. The variation in registration time, registration error, and the participants' perception of difficulty was analyzed. It was found that, contrary to what might be initially assumed, the use of targets does not reduce the registration time nor does it result in greater difficulty when processed, provided that the registration technicians have sufficient experience and the field captures were performed considering the reduction of occlusions. On the other hand, as expected, it significantly reduces the registration error from an average value of 0.0116 m to 0.0089 m. These results are useful for those who perform field captures with point clouds using terrestrial laser scanners and wish to improve field accuracy in exchange for considering the time required for target manipulation in the field.

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Author Biographies

Luis Carlos Cruz-Ramírez, Laboratorio de Posgrado, Escuela Superior de Ingeniería y Arquitectura, Unidad Tecamachalco, Instituto Politécnico Nacional

Arquitecto por la Universidad Nacional de Ingeniería (UNI RUSB), Managua, Nicaragua (2004-2009). Maestro (2012-2015) y Doctor en Ciencias en Arquitectura y Urbanismo (2016-2018), por la Escuela Superior de Ingeniería y Arquitectura, Unidad Tecamachalco (ESIA, TEC), del Instituto Politécnico Nacional (IPN). Posdoctorado en Desarrollo de Tecnologías para la Gestión del Riesgo de Inundaciones ante el Cambio Climático por IPN, University of Edinburgh y Heriot-Watt University (2019-2022). Realizó estancia de investigación en la Università degli “G. d'Annunzio”, Pescara, Abruzzo, Italia, para estudiar Integraciones Contemporáneas en Contextos Históricos (2017). Elaboró proyectos ejecutivos para DIARSA (2010-2012) y Video Mapping para Managua-LAB (2011-2012). Desde 2022 es Coordinador de Laboratorios de Posgrado de la ESIA TEC del IPN .

Jorge Fernando Zárate-Martínez, Laboratorio de Posgrado, Escuela Superior de Ingeniería y Arquitectura, Unidad Tecamachalco, Instituto Politécnico Nacional.

Licenciado en Psicología Social por la UAM-Iztapalapa, Ciudad de México (1980-1986), Egresado de la Maestría en Psicología Universidad Iberoamericana (1987-1990). Docente del Instituto Politécnico Nacional (IPN), México de 1977-1991 y de 2006- a la actualidad. Además es docente a nivel licenciatura en la Universidad Iberoamericana, y en la Universidad Latinoamericana. Es Presidente de la Academia de inglés, en la Escuela Superior de Ingeniería y Arquitectura Unidad Tecamachalco (ESIA TEC) del IPN. Es coordinador de Movilidad e Internacionalización del Posgrado de ESIA TEC del IPN. Es director de AB Center Inglés. Speaking Examiner para Cambridge University (Cambridge English Assessment), en niveles pre-A1, A1, A2, B1, B2, C1 y BEC Preliminary (B1 business).

References

EDF. (2024). Cloud Compare (2.13.2 Kharkiv) [Computer Software]. Obtenido de https://www.cloudcompare.org

Akca, D., & Gruen, A. (2007). Generalized least squares multiple 3D surface matching. ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007. Espoo, Finland: IAPRS. Obtenido de https://foto.aalto.fi/ls2007/presentations/Akca_ls2007_presentation.pdf

Aryan, A., Bosché, F., & Tang, P. (2021). Planning for terrestrial laser scanning in construction: A review. Automation in Construction(125). doi:10.1016/j.autcon.2021.103551

Barber, D. M., Dallas, R. W., & J Mills, o. P. (2006). Laser Scanning for Architectural Conservation. Journal of Architectural Conservation, 12(1), 35-52. doi:10.1080/13556207.2006.10784959

Bosché, F. (2012). Plane-based registration of construction laser scans with 3D/4D building models. Advanced Engineering Informatics, 26, 90-102. doi:10.1016/j.aei.2011.08.009

Cabrera-Revuelta, E., Tavolare, R., Buldo, M., & Versoscia, C. (2024). Planning for terrestrial laser scanning: Methods for optimal sets of locations in architectural sites. Journal of Building Engineering, 85, 1-19. doi:https://doi.org/10.1016/j.jobe.2024.108599

Cheng, L., Chen, S., Liu, X., Xu, H., Wu, Y., Li, M., & Chen, Y. (2018). Registration of Laser Scanning Point Clouds: A Review. Sensors, 18(1641), 1-25. doi:10.3390/s18051641

Cox, R. A. (2015). Real-world comparisons between target-based and targetless point-cloud registration in FARO Scene, Trimble RealWorks and Autodesk Recap [Bachelor Dissertation]. University of Southern Queensland. Obtenido de https://sear.unisq.edu.au/29195/1/Cox_R_Zhang.pdf

Dong, Z., Liang, F., Yang, B., Xu, Y., Zang, Y., Li, J., . . . Stilla, U. (2020). Registration of large-scale terrestrial laser scanner point clouds: A review and benchmark. ISPRS Journal of Photogrammetry and Remote Sensing, 163, 327-342. doi:https://doi.org/10.1016/j.isprsjprs.2020.03.013

Gu, X., Wang, X., & Guo, Y. (2020). A Review of Research on Point Cloud Registration Methods. IOP Conf. Series: Materials Science and Engineering, 782. doi:10.1088/1757-899X/782/2/022070

Keitaanniemi, A., Virtanen, J.-P., Rönnholm, P., Kukko, A., Rantanen, T., & Vaaja, M. (2021). The Combined Use of SLAM Laser Scanning and TLS for the 3D Indoor Mapping. Building, 11(386), 1-18. doi:10.3390/buildings11090386

Leica Geosystems. (2014). Cyclone V9.0 [Computer Software]. Obtenido de https://leica-geosystems.com/de-at/blog-content/2014/leica-cyclone-9

Leica Geosystems. (10 de 2025). Leica ScanStation C10. Obtenido de Leica Scanstation C10: https://cpec.leica-geosystems.com/es/producto/leica-scanstation-c10/

Liu, Y. (2006). Automatic Registration of overlapping 3D point clouds using closest points. Imagen and Vision Computing(24), 762-781. doi:10.1016/j.imavis.2006.01.009

Mill, T., Alt, A., & Liias, R. (2013). Combining 3D Building Surveying Techniques - Terrestrial Laser Scanning (TLS) And Total Station Suveying for BIM Data Management Purposes. Journal of Civil Engineering and Management, 19, 23-32. doi:10.3846/13923730.2013.795187

Remondino, F. (2011). Heritage Recording and 3D modeling with photogrammetry and 3d scanning. Reomete Sensing(3), 1104-1138. doi:10.3390/rs3061104

Urbančič, T., Roškar, Ž., Kosmatin Fras, M., & Grigillo, D. (2019). New Target for Accurate Terrestrial Laser Scanning and Unmanned Aerial Vehicle Point Cloud Registration. Sensors, 19(14). doi:https://doi.org/10.3390/s19143179

Published

2025-12-19

How to Cite

Cruz-Ramírez, L. C., & Zárate-Martínez, J. F. (2025). Using targets in fieldwork with TLS and its implications on the coarse registration . Architecture + Journal, 10(20), 82–96. https://doi.org/10.5377/arquitectura.v10i20.21775

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