Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1
Harald Sternberg
 -- 1064 2023-12-29 11:04:33 |
2 references update
Fanny Huang
 Meta information modification 1064 2024-01-02 09:53:16 |

Video Upload Options

Do you have a full video?
Send video materials Upload full video

Confirm

Are you sure to Delete?
Yes No
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Askar, C.; Sternberg, H. Smartphone Lidar Technology for Low-Cost 3D Building Documentation. Encyclopedia. Available online: https://encyclopedia.pub/entry/53269 (accessed on 07 May 2024).
Askar C, Sternberg H. Smartphone Lidar Technology for Low-Cost 3D Building Documentation. Encyclopedia. Available at: https://encyclopedia.pub/entry/53269. Accessed May 07, 2024.
Askar, Cigdem, Harald Sternberg. "Smartphone Lidar Technology for Low-Cost 3D Building Documentation" Encyclopedia, https://encyclopedia.pub/entry/53269 (accessed May 07, 2024).
Askar, C., & Sternberg, H. (2023, December 29). Smartphone Lidar Technology for Low-Cost 3D Building Documentation. In Encyclopedia. https://encyclopedia.pub/entry/53269
Askar, Cigdem and Harald Sternberg. "Smartphone Lidar Technology for Low-Cost 3D Building Documentation." Encyclopedia. Web. 29 December, 2023.
Smartphone Lidar Technology for Low-Cost 3D Building Documentation
Edit
This entry is adapted from the peer-reviewed paper 10.3390/geomatics3040030

Laser scanning technology has long been the preferred method for capturing interior scenes in various industries. With a growing market, smaller and more affordable scanners have emerged, offering end products with sufficient accuracy. While not on par with professional scanners, Apple has made laser scanning technology accessible to users with the introduction of the new iPhone Pro models, democratizing 3D scanning.

3D scanning smartphones lidar

1. Introduction

Over the past decades, laser scanning has emerged as a cutting-edge technology. Laser scanners generate point clouds that are highly effective in representing objects of varying complexity at different scales [1]. In the 1990s, terrestrial laser scanners (TLS) were introduced to the surveying industry [2], and towards the 2010s, they became more accurate and capable of scanning ranges of hundreds of meters. TLSs are widely used in a variety of applications, including cultural heritage [3][4], change detection [5][6], monitoring and deformation [7][8][9], as-built modelling [10], and forestry [11]. In the late 2000s, mobile mapping systems (MMS), which operate on a vehicle such as a car, were introduced into mapping operations, mainly for data capture on road infrastructure and building facades [12] and extended its use to various applications [13][14][15][16][17][18][19][20].
These systems utilize active or passive sensing to capture the object of interest, along with GNSS and IMU for accurate georeferencing. While the GNSS and IMU combination works well for outdoor applications, in GNSS-denied spaces like indoors, using only inertial sensors leads to an increasing drift rate, one which cannot be corrected due to the unknown function with respect to time [21]. Simultaneous localization and mapping (SLAM) is one of the techniques that offers a solution to this problem. Its fundamental concept is monitoring the sensor’s position and orientation (pose) over time in 3 degrees of freedom (DoF) and with relative coordinates, respectively. This is achieved by utilizing overlaps in optical data, such as with previously observed features [21].
Nowadays, numerous low-cost MMS rely on SLAM and can be utilized through various platforms like trolleys, backpacks, and hand-held devices. Although many of these systems have been initialized for entertainment, some have led to research work developments for further applications. In addition to mobile laser scanner solutions, depth cameras represent another commonly employed low-cost alternative in 3D documentation. The integration of RGB and depth cameras generates a 3D representation of the scene by capturing the distance between the object and the camera within their field of view (FOV) and is frequently utilized in computer vision [22]. Two common approaches for depth cameras are time-of-flight (ToF) and structured light. ToF cameras, exemplified by devices like Azure Kinect and HoloLens, emit light pulses and capture the reflected signal to calculate the distance based on the measured time for the light to travel to an object and back. Numerous studies have incorporated both systems in indoor mapping [23][24][25]. Structured light-based cameras project a known light pattern onto the scene and calculate depth information based on the distortion of the pattern on the analyzed object surface. Early generations of Kinect serve as a well-known example of this type of camera and have been utilized in various studies to investigate their capabilities in indoor mapping [22][26][27].
The developments in laser scanning technology and the rapid advancement in low-cost sensor technology have made 3D laser scanning more accessible and cost-effective. Over the years, researchers have investigated comparative evaluation of the lidar-based indoor MSS, such as [28][29][30][31]. Even consumer technology, like some iPhone models, now incorporates laser scanning technology, opening possibilities for the democratization of 3D scanning. 

2. Smartphone Lidar Technology for Low-Cost 3D Building Documentation

Using smartphones to obtain spatial information is not a new concept, as smartphones are equipped with inertial sensors that are commonly used in indoor positioning, such as in [32], and cameras that are used in 3D reconstruction based on images or videos [33][34]. Most earlier studies intensively worked with the Google Tango technology, which was launched in 2014 [35] and aimed to evaluate the dependability, influence, and engagement of users in a hardware and software bundle that permits the development of augmented/mixed/virtual reality content exclusively through the use of their smartphones or tablets [36]. The Tango project was only available on a limited number of compatible phones and tablets. In 2018, the project was terminated and replaced with ARCore [37]. Some studies include [38][39], both of which tested the Tango tablet’s capability for 3D documentation of indoor spaces. Other examples are [40], which investigated 3D reconstruction using a Tango smartphone in the context of cultural heritage, and [36], which assessed the quality and potential of the system in their study.
Apple introduced lidar sensors into its pro lines of tablets and smartphones, iPad Pro and iPhone 12 Pro, in 2020. This brought a novelty to the 3D scanning subject by incorporating a lidar sensor into user-grade smartphones, leading to the question of whether these devices would be a low-cost alternative with enough accuracy in 3D scanning. Apple’s aim was more to improve the camera and enhance the augmented reality experience for its users. Hence, Apple has not released any 3D scanning applications for large spaces or objects after the initial release, apart from the Measure app, which is designed as a measuring tool. However, Apple has provided a software development kit (SDK); since then, many developers have developed 3D scanning apps with ARKit by Apple. As it seems to be compatible with novice users who seek to generate a floor plan to design their houses or to try furniture before buying, more applications that target scanning experts have been released over time. It has also received attention from researchers as a low-cost and over-the-shelf alternative for 3D documentation. Different subjects have been investigated since the release of the first Apple device equipped with the lidar sensor. [41][42] evaluated the iPhone 12 Pro for its use in geoscience applications. The former reports a 10 cm sensor accuracy when demonstrating its use on a coastal cliff, while the latter concludes that the tested iPhone 12 Pro device would be the standard process for capturing rocky slopes and investigating discontinuities, despite limitations in its range. [43][44] assessed the Apple lidar devices for their use in heritage documentation and concluded that this technology holds great promise for the near future. [45] investigated these devices for indoor/outdoor modelling and reported 53 cm for local precision and 10 cm for global correctness. The indoor test space consisted of two adjacent rooms that covered a total of around 200 m2. [46] evaluated the iPad Pro from the architectural surveying perspective and reported 2 cm precision and 4 cm accuracy for a 1:200 map scale.

References

  1. Di Stefano, F.; Chiappini, S.; Gorreja, A.; Balestra, M.; Pierdicca, R. Mobile 3D scan LiDAR: A literature review. Geomatics Nat. Hazards Risk 2021, 12, 2387–2429.
  2. Scantech International. Timeline of 3D Laser Scanners | By Scantech International. Available online: https://scantech-international.com/blog/timeline-of-3d-laser-scanners (accessed on 3 March 2023).
  3. Pritchard, D.; Sperner, J.; Hoepner, S.; Tenschert, R. Terrestrial laser scanning for heritage conservation: The Cologne Cathedral documentation project. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2017, IV-2/W2, 213.
  4. Kushwaha, S.K.P.; Dayal, K.R.; Sachchidanand; Raghavendra, S.; Pande, H.; Tiwari, P.S.; Agrawal, S.; Srivastava, S.K. 3D Digital Documentation of a Cultural Heritage Site Using Terrestrial Laser Scanner—A Case Study. In Applications of Geomatics in Civil Engineering, 1st ed.; Lecture Notes in Civil Engineering; Ghosh, J.K., da Silva, I., Eds.; Springer: Singapore, 2020; Volume 33, pp. 49–58.
  5. Lague, D.; Brodu, N.; Leroux, J. Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (N-Z). ISPRS J. Photogramm. Remote Sens. 2013, 82, 10–26.
  6. Schürch, P.; Densmore, A.L.; Rosser, N.J.; Lim, M.; McArdell, B.W. Detection of surface change in complex topography using terrestrial laser scanning: Application to the Illgraben debris-flow channel. Earth Surf. Process. Landf. 2011, 36, 1847–1859.
  7. Sternberg, H. Deformation Measurements at Historical Buildings with Terrestrial Laserscanners. In Proceedings of the ISPRS Commission V Symposium Image Engineering and Vision Metrology, Dresden, Germany, 25–27 September 2006; pp. 303–308. Available online: https://www.isprs.org/proceedings/xxxvi/part5/paper/STER_620.pdf (accessed on 17 July 2023).
  8. Wang, W.; Zhao, W.; Huang, L.; Vimarlund, V.; Wang, Z. Applications of terrestrial laser scanning for tunnels: A review. J. Traffic Transp. Eng. (Eng. Ed.) 2014, 1, 325–337.
  9. Mukupa, W.; Roberts, G.W.; Hancock, C.M.; Al-Manasir, K. A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures. Surv. Rev. 2017, 49, 99–116.
  10. Raza, M. BIM for Existing Buildings: A Study of Terrestrial Laser Scanning and Conventional Measurement Technique. Master’s Thesis, Metropolia University of Applied Sciences, Helsinki, Finland, 2017.
  11. Park, H.; Lim, S.; Trinder, J.; Turner, R. 3D surface reconstruction of Terrestrial Laser Scanner data for forestry. In Proceedings of the IGARSS 2010–2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, HI, USA, 25–30 July 2010; pp. 4366–4369.
  12. Petrie, G. An Introduction to the Technology Mobile Mapping Systems. GeoInformatics 2016, 13, 32–43. Available online: http://petriefied.info/Petrie_Mobile_Mapping_Systems_Jan-Feb_2010.pdf (accessed on 17 July 2023).
  13. Hamraz, H.; Contreras, M.A.; Zhang, J. Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds. Sci. Rep. 2017, 7, 6770.
  14. Chen, D.; Wang, R.; Peethambaran, J. Topologically Aware Building Rooftop Reconstruction From Airborne Laser Scanning Point Clouds. IEEE Trans. Geosci. Remote Sens. 2017, 55, 7032–7052.
  15. Toth, C.; Grejner-Brzezinska, D. Redefining the Paradigm of Modern Mobile Mapping. Photogramm. Eng. Remote Sens. 2004, 70, 685–694.
  16. Briese, C.; Zach, G.; Verhoeven, G.; Ressl, C.; Ullrich, A.; Studnicka, N.; Doneus, M. Analysis of mobile laser scanning data and multi-view image reconstruction. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2012, XXXIX-B5, 163–168.
  17. Stojanovic, V.; Shoushtari, H.; Askar, C.; Scheider, A.; Schuldt, C.; Hellweg, N.; Sternberg, H. A Conceptual Digital Twin for 5G Indoor Navigation. 2021. Available online: https://www.researchgate.net/publication/351234064 (accessed on 30 November 2023).
  18. Ibrahimkhil, M.H.; Shen, X.; Barati, K.; Wang, C.C. Dynamic Progress Monitoring of Masonry Construction through Mobile SLAM Mapping and As-Built Modeling. Buildings 2023, 13, 930.
  19. Mahdjoubi, L.; Moobela, C.; Laing, R. Providing real-estate services through the integration of 3D laser scanning and building information modelling. Comput. Ind. 2013, 64, 1272–1281.
  20. Sgrenzaroli, M.; Barrientos, J.O.; Vassena, G.; Sanchez, A.; Ciribini, A.; Ventura, S.M.; Comai, S. Indoor mobile mapping systems and (bim) digital models for construction progress monitoring. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2022, XLIII-B1-2, 121–127.
  21. Lehtola, V.V.; Nikoohemat, S.; Nüchter, A.; Lehtola, V.V.; Nikoohemat, S.; Nüchter, A. Indoor 3D: Overview on Scanning and Reconstruction Methods. In Handbook of Big Geospatial Data; Werner, M., Chiang, Y.-Y., Eds.; Springer: Berlin, Germany, 2021; pp. 55–97.
  22. Lachat, E.; Macher, H.; Mittet, M.-A.; Landes, T.; Grussenmeyer, P. First experiences with kinect v2 sensor for close range 3d modelling. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2015, XL-5/W4, 93–100.
  23. Khoshelham, K.; Tran, H.; Acharya, D. Indoor mapping eyewear: Geometric evaluation of spatial mapping capability of hololens. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2019, XLII-2/W13, 805–810.
  24. Delasse, C.; Lafkiri, H.; Hajji, R.; Rached, I.; Landes, T. Indoor 3D Reconstruction of Buildings via Azure Kinect RGB-D Camera. Sensors 2022, 22, 9222.
  25. Hübner, P.; Clintworth, K.; Liu, Q.; Weinmann, M.; Wursthorn, S. Evaluation of HoloLens Tracking and Depth Sensing for Indoor Mapping Applications. Sensors 2020, 20, 1021.
  26. Weinmann, M.; Wursthorn, S.; Jutzi, B. Semi-automatic image-based co-registration of range imaging data with different characteristics. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2013, XXXVIII-3, 119–124.
  27. Kalantari, M.; Nechifor, M. 3D Indoor Surveying—A Low Cost Approach. Surv. Rev. 2016, 49, 1–6.
  28. Lehtola, V.V.; Kaartinen, H.; Nüchter, A.; Kaijaluoto, R.; Kukko, A.; Litkey, P.; Honkavaara, E.; Rosnell, T.; Vaaja, M.T.; Virtanen, J.-P.; et al. Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods. Remote Sens. 2017, 9, 796.
  29. Tucci, G.; Visintini, D.; Bonora, V.; Parisi, E.I. Examination of Indoor Mobile Mapping Systems in a Diversified Internal/External Test Field. Appl. Sci. 2018, 8, 401.
  30. di Filippo, A.; Sánchez-Aparicio, L.J.; Barba, S.; Martín-Jiménez, J.A.; Mora, R.; Aguilera, D.G. Use of a Wearable Mobile Laser System in Seamless Indoor 3D Mapping of a Complex Historical Site. Remote Sens. 2018, 10, 1897.
  31. Salgues, H.; Macher, H.; Landes, T. Evaluation of mobile mapping systems for indoor surveys. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2020, XLIV-4/W1-2020, 119–125.
  32. Shoushtari, H.; Willemsen, T.; Sternberg, H. Many Ways Lead to the Goal—Possibilities of Autonomous and Infrastructure-Based Indoor Positioning. Electronics 2021, 10, 397.
  33. Tanskanen, P.; Kolev, K.; Meier, L.; Camposeco, F.; Saurer, O.; Pollefeys, M. Live Metric 3D Reconstruction on Mobile Phones. In Proceedings of the 2013 IEEE International Conference on Computer Vision (ICCV), Sydney, Australia, 1–8 December 2013; pp. 65–72.
  34. Kersten, T.P. The Smartphone as a Professional Mapping Tool | GIM International. GIM International, 25 February 2020. Available online: https://www.gim-international.com/content/article/the-smartphone-as-a-professional-mapping-tool (accessed on 17 July 2023).
  35. Wikipedia. Tango (Platform)-Wikipedia. Available online: https://en.wikipedia.org/wiki/Tango_(platform) (accessed on 10 May 2023).
  36. Bianchini, C.; Catena, L. The Democratization of 3D Capturing an Application Investigating Google Tang Potentials. Int. J. Bus. Hum. Soc. Sci. 2019, 12, 3298576.
  37. Google. Build New Augmented Reality Experiences that Seamlessly Blend the Digital and Physical Worlds | ARCore | Google Developers. Available online: https://developers.google.com/ar (accessed on 10 May 2023).
  38. Diakité, A.A.; Zlatanova, S. First experiments with the tango tablet for indoor scanning. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2016, III-4, 67–72.
  39. Froehlich, M.; Azhar, S.; Vanture, M. An Investigation of Google Tango® Tablet for Low Cost 3D Scanning. In Proceedings of the 34th International Symposium on Automation and Robotics in Construction, Taipei, Taiwan, 28 June–1 July 2017; pp. 864–871.
  40. Boboc, R.G.; Gîrbacia, F.; Postelnicu, C.C.; Gîrbacia, T. Evaluation of Using Mobile Devices for 3D Reconstruction of Cultural Heritage Artifacts. In VR Technologies in Cultural Heritage; Duguleană, M., Carrozzino, M., Gams, M., Tanea, I., Eds.; Communications in Computer and Information Science; Springer International Publishing: Cham, Swizterland, 2019; Volume 904, pp. 46–59.
  41. Luetzenburg, G.; Kroon, A.; Bjørk, A.A. Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences. Sci. Rep. 2021, 11, 1–9.
  42. Riquelme, A.; Tomás, R.; Cano, M.; Pastor, J.L.; Jordá-Bordehore, L. Extraction of discontinuity sets of rocky slopes using iPhone-12 derived 3DPC and comparison to TLS and SfM datasets. IOP Conf. Ser. Earth Environ. Sci. 2021, 833, 012056.
  43. Murtiyoso, A.; Grussenmeyer, P.; Landes, T.; Macher, H. First assessments into the use of commercial-grade solid state lidar for low cost heritage documentation. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2021, XLIII-B2-2, 599–604.
  44. Losè, L.T.; Spreafico, A.; Chiabrando, F.; Tonolo, F.G. Apple LiDAR Sensor for 3D Surveying: Tests and Results in the Cultural Heritage Domain. Remote Sens. 2022, 14, 4157.
  45. Díaz-Vilariño, L.; Tran, H.; Frías, E.; Balado, J.; Khoshelham, K. 3D mapping of indoor and outdoor environments using Apple smart devices. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2022, XLIII-B4-2, 303–308.
  46. Spreafico, A.; Chiabrando, F.; Losè, L.T.; Tonolo, F.G. The ipad pro built-in lidar sensor: 3D rapid mapping tests and quality assessment. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2021, XLIII-B1-2, 63–69.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Others
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Cigdem Askar
,
Harald Sternberg
View Times: 183
Revisions: 2 times (View History)
Update Date: 02 Jan 2024
Table of Contents
    1000/1000
    Hot Most Recent
    Feedback