Skip to main content

3D Object Reconstruction Using Concatenated Matrices with MS Kinect: A Contribution to Interiors Architecture

  • Conference paper
  • First Online:
Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Abstract

Interior architecture is part of the individual, social and business life of the human being; it allows structuring the spaces to inhabit, study or work. This document presents the design and implementation of a system that allows the three-dimensional reconstruction of objects with a reduced economic investment. The image acquisition process and treatment of the information with mathematical support that it entails are described. The system involves an MS Kinect as a tool to create a radar that operates with the structured light principle to capture objects at a distance of less than 2 meters. The development of the scripts is done in the MATLAB software and in the same way the graphical interface that is presented to the user. As part of the initial tests of this prototype, the digitization of geometric shape structures has been performed with an accuracy of over 98%. This validates its efficient operation, which serves as the basis for the development of modeling in interior architecture for future work.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Fernández-S, Á., Salazar-L, F., Jurado, M., Castellanos, E.X., Moreno-P, R., Buele, J.: Electronic system for the detection of chicken eggs suitable for incubation through image processing. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S. (eds.) WorldCIST’19 2019. AISC, vol. 931, pp. 208–218. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-16184-2_21

    Chapter  Google Scholar 

  2. Hugeng, H., Anggara, J., Gunawan, D.: Implementation of 3D HRTF interpolation in synthesizing virtual 3D moving sound. Int. J. Technol. (2017). https://doi.org/10.14716/ijtech.v8i1.6859

  3. Elsayed, M., Soe, M.T., Kit, W.W., Abdalla, H.: An innovative approach to developing a 3D virtual map creator using an ultrasonic sensor array. Int. J. Technol. (2019). https://doi.org/10.14716/ijtech.v10i7.3245

  4. Protasov, A.: Active infrared testing of composites using 3D computer simulation. Int. J. Technol. (2018). https://doi.org/10.14716/ijtech.v9i3.218

  5. Taylor, M.: Lifshitz holography. Class. Quantum Gravity (2016). https://doi.org/10.1088/0264-9381/33/3/033001

  6. Chiani, M., Giorgetti, A., Paolini, E.: Sensor Radar for object tracking (2018). https://doi.org/10.1109/JPROC.2018.2819697

  7. Meinl, F., Stolz, M., Kunert, M., Blume, H.: An experimental high performance radar system for highly automated driving. In: 2017 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility, ICMIM 2017 (2017). https://doi.org/10.1109/ICMIM.2017.7918859

  8. Moreno Avilés, D., Mejía, J., Moreno, H.: Desarrollo de un algoritmo en MATLAB para la optimización de la resolución de una tarjeta USRP B210 para aplicaciones SDRadar. MASKAY (2017). https://doi.org/10.24133/maskay.v7i1.338

  9. Iakushkin, O., Selivanov, D., Tazieva, L., Fatkina, A., Grishkin, V., Uteshev, A.: 3D reconstruction of landscape models and archaeological objects based on photo and video materials. In: Gervasi, O., et al. (eds.) ICCSA 2018. LNCS, vol. 10963, pp. 160–169. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95171-3_14

    Chapter  Google Scholar 

  10. Capece, N., Erra, U., Romaniello, G.: A low-cost full body tracking system in virtual reality based on microsoft kinect. In: De Paolis, L.T., Bourdot, P. (eds.) AVR 2018. LNCS, vol. 10851, pp. 623–635. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95282-6_44

    Chapter  Google Scholar 

  11. Rosell-Polo, J.R., et al..: Kinect v2 sensor-based mobile terrestrial laser scanner for agricultural outdoor applications. IEEE/ASME Trans. Mechatron. (2017). https://doi.org/10.1109/TMECH.2017.2663436

  12. Pritchard, M.E., Yun, S.-H.: Satellite radar imaging and its application to natural hazards. In: Natural Hazards (2018). https://doi.org/10.1201/9781315166841-5

  13. Jordan, S., et al.: State-of-the-art technologies for UAV inspections, (2018). https://doi.org/10.1049/iet-rsn.2017.0251

  14. Riaz, M., Bukhari, S.A., Mukhtar, F., Kamal, T., Sarwar, H., Tahir, M.U.: 3D mapping using light detection and ranging. In: Proceedings of 2017 International Multi-Topic Conference, INMIC 2017 (2018). https://doi.org/10.1109/INMIC.2017.8289468

  15. Anwer, A., Ali, S.S.A., Meriaudeau, F.: Underwater online 3D mapping and scene reconstruction using low cost kinect RGB-D sensor. In: International Conference on Intelligent and Advanced Systems, ICIAS 2016 (2017). https://doi.org/10.1109/ICIAS.2016.7824132

  16. Minda Gilces, D., Matamoros Torres, K.: A kinect-based gesture recognition approach for the design of an interactive tourism guide application. In: Communications in Computer and Information Science (2018)

    Google Scholar 

  17. Ishida, K.: Construction progress management and interior work analysis using kinect 3D image sensors. In: ISARC 2016 - 33rd International Symposium on Automation and Robotics in Construction (2016)

    Google Scholar 

  18. Barberán, J., et al.: Radar system for the reconstruction of 3D objects: a preliminary study. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S., Orovic, I., Moreira, F. (eds.) WorldCIST 2020. AISC, vol. 1160, pp. 238–247. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-45691-7_23

    Chapter  Google Scholar 

Download references

Acknowledgments

A special thanks to the Universidad Tecnológica Indoamérica for supporting the development of this work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jorge Buele .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Buele, J., Varela-Aldás, J., Castellanos, E.X., Jadán-Guerrero, J., Barberán, J. (2020). 3D Object Reconstruction Using Concatenated Matrices with MS Kinect: A Contribution to Interiors Architecture. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12254. Springer, Cham. https://doi.org/10.1007/978-3-030-58817-5_49

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-58817-5_49

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58816-8

  • Online ISBN: 978-3-030-58817-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics