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   1. <dc:title>3D Object Reconstruction Using Concatenated Matrices with MS Kinect: A Contribution to Interiors Architecture</dc:title>

   2. <dc:creator>Buele, Jorge (1)</dc:creator>

   3. <dc:creator>Varela-Aldás, José</dc:creator>

   4. <dc:creator>Castellanos, Esteban X.</dc:creator>

   5. <dc:creator>Jadán-Guerrero, Janio</dc:creator>

   6. <dc:creator>Barberán, Jeneffer</dc:creator>

   7. <dc:subject>3D object reconstruction</dc:subject>

   8. <dc:subject>combined matrix</dc:subject>

   9. <dc:subject>image processing</dc:subject>

   10. <dc:subject>interior architecture</dc:subject>

   11. <dc:subject>software applications</dc:subject>

   12. <dc:subject>Scopus(2)</dc:subject>

   13. <dc:subject>WOS(2)</dc:subject>

   14. <dc:description>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.</dc:description>

   15. <dc:date>2020</dc:date>

   16. <dc:date>2021-07-28T10:54:09Z</dc:date>

   17. <dc:date>2021-07-28T10:54:09Z</dc:date>

   18. <dc:type>conferenceObject</dc:type>

   19. <dc:identifier>9783030588168</dc:identifier>

   20. <dc:identifier>0302-9743</dc:identifier>

   21. <dc:identifier>https://reunir.unir.net/handle/123456789/11681</dc:identifier>

   22. <dc:identifier>https://doi.org/10.1007/978-3-030-58817-5_49</dc:identifier>

   23. <dc:language>eng</dc:language>

   24. <dc:relation>;vol. 12254</dc:relation>

   25. <dc:relation>https://link.springer.com/chapter/10.1007%2F978-3-030-58817-5_49</dc:relation>

   26. <dc:rights>restrictedAccess</dc:rights>

   27. <dc:publisher>Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics)</dc:publisher>

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