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Virtual Reconstruction of Objects by Point Cloud Capture to Measurement of Density Parameters Using Low Cost Device

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Human-Computer Interaction (HCI-COLLAB 2021)

Abstract

It is studied in this project the viability to implement an application to virtually rebuild objects using a low-cost device. A rebuilding application was developed using ReconstructMe SDK’s interfaces and a Kinect as a depth device. An analysis tool working on the Unity engine was also implemented, operating mainly as Editor Scripting with its C# API feature. This tool implements the capacity to obtain the measurement data of volumetric extremes of the virtual objects. The proposal is tested by rebuilding of some specific objects, which are the closest resource; by manually conducting the device. With results, the application faces some problems with the mesh fitting of some objects, however the mesh quality is relatively good. Based on data measured, it is achieved a good level of precision on the extreme measures besides that each rebuilding procedure can be made within a relatively fast time cost, around 25 s.

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References

  1. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 4th edn. Pearson, New York (2018)

    Google Scholar 

  2. Alves, G.T.M.: A study of techniques for shape acquisition using stereo and structured light aimed for engineering. Thesis, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, Brazil (2005)

    Google Scholar 

  3. Vasconcelos, C.N.: Image processing and computer vision algorithms for graphics cards parallel architectures. Thesis, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, Brazil (2009)

    Google Scholar 

  4. Haibo, Y.: Industrial design applications of surface reconstruction algorithm based on three dimensional point cloud data. In: 2017 International Conference on Robots & Intelligent System (ICRIS), pp. 178–181. IEEE (2017)

    Google Scholar 

  5. Zhang, R., Wang, Y., Song, D.: Research and implementation from point cloud to 3D model. In: 2010 Second International Conference on Computer Modeling and Simulation, pp. 169–172. IEEE (2010)

    Google Scholar 

  6. Heindl, C., Bauer, H., Ankerl, M., Pichler, A.: ReconstructMe SDK: a C API for Real-time 3D scanning. In: 6th International Conference and Exhibition on 3D Body Scanning Technologies, pp. 185–193. Hometrica Consulting - Dr. Nicola D’Apuzzo, Ascona, Switzerland (2015)

    Google Scholar 

  7. Chikurtev, D., Rangelov, I., Chivarov, N., Karastoyanov, D.: 3D modelling for object recognition with depth sensors. Probl. Eng. Cybern. Robot. 70, 35–42 (2018). Accessed 07 Sept 2020. http://www.iict.bas.bg/pecr/index.html

  8. Rafibakhsh, N., Gong, J., Siddiqui, M.K., Gordon, C., Lee, H.F.: Analysis of XBOX kinect sensor data for use on construction sites: depth accuracy and sensor interference assessment. In: Construction Research Congress 2012, pp. 848–857. American Society of Civil Engineers, Reston (2012)

    Google Scholar 

  9. DiFilippo, N.M., Jouaneh, M.K.: Characterization of different microsoft kinect sensor models. IEEE Sens. J. 15, 4554–4564 (2015)

    Article  Google Scholar 

  10. Han, J., Shao, L., Xu, D., Shotton, J.: Enhanced computer vision with Microsoft kinect sensor: a review. IEEE Trans. Cybern. 43, 1318–1334 (2013)

    Article  Google Scholar 

  11. Andersen, M.R., Jensen, T., Lisouski, P., Mortensen, A.K., Hansen, M.K., Gregersen, T., Ahrendt, P.: Kinect depth sensor evaluation for computer vision applications. Aarhus Univ, pp. 1–37 (2012)

    Google Scholar 

  12. Khoshelham, K.: Accuracy analysis of kinect depth data. In: ISPRS Workshop Laser Scanning, pp. 133–138 (2011)

    Google Scholar 

  13. Khan, W., Phaisangittisagul, E., Ali, L., Gansawat, D., Kumazawa, I.: Combining features for RGB-D object recognition. In: 2017 International Electrical Engineering Congress (iEECON), pp. 1–5. IEEE (2017)

    Google Scholar 

  14. Smisek, J., Jancosek, M., Pajdla, T.: 3D with kinect. In: Fossati, A., Gall, J., Grabner, H., Ren, X., Konolige, K. (eds.) Consumer Depth Cameras for Computer Vision, pp. 3–25. Springer, London (2013)

    Chapter  Google Scholar 

  15. Zhang, Z.: Microsoft kinect sensor and its effect. IEEE Multimed. 19, 4–10 (2012)

    Article  Google Scholar 

  16. Liu, H., Zhang, X., Wang, S., Chen, L.: The reconstruction of three-dimensional tree models from terrestrial LiDAR. In: 2011 IEEE International Conference on Computer Science and Automation Engineering. pp. 371–374. IEEE (2011)

    Google Scholar 

  17. Pérez-Ruiz, M., Tarrat-Martín, D., Sánchez-Guerrero, M.J., Valera, M.: Advances in horse morphometric measurements using LiDAR. Comput. Electron. Agric. 174, 105510 (2020)

    Article  Google Scholar 

  18. Xu, Q., Wang, J., An, X.: A pipeline for surface reconstruction of 3-dimentional point cloud. In: 2014 International Conference on Audio, Language and Image Processing, pp. 822–826. IEEE, Shanghai (2014)

    Google Scholar 

  19. Donofre, A.C., Puoli Filho, J.N.P., Ferreira, I.E.D.P., Mota, M.D.S.D., Chiquitelli Neto, M.: Equilíbrio de cavalos da raça Quarto de Milha participantes da modalidade de três tambores por meio de proporções corporais. Ciência Rural. 44, 327–332 (2014)

    Google Scholar 

  20. Lage, M.C.G.R., Bergmann, J.A.G., Procópio, A.M., Pereira, J.C.C., Biondini, J.: Associação entre medidas lineares e angulares de equinos da raça Mangalarga Marchador. Arq. Bras. Med. Veterinária e Zootec. 61, 968–979 (2009)

    Article  Google Scholar 

  21. Santiago, J.M., Rezende, A.S.C., Fonseca, M.G., Abrantes, R.G.P., Lage, J., Lana, Â.M.Q.: Comparação entre as medidas morfométricas do rebanho atual de machos Mangalarga Marchador e dos campeões da raça. Bol. Indústria Anim. 70, 46–52 (2013)

    Article  Google Scholar 

  22. Pasternak, M., Kahani, N., Bagherzadeh, M., Dingel, J., Cordy, J.R.: SimGen: a tool for generating simulations and visualizations of embedded systems on the unity game engine. In: 21st ACM/IEEE International Conference Model Driven Engineering Language System Companion Proceedings, Model, pp. 42–46 (2018)

    Google Scholar 

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Acknowledgments

Acknowledgments to the “Instituto Federal Goiano (IF Goiano)”, especially to the Morrinhos institution campus, and the science initiation program “Programa Institucional Voluntário de Iniciação Científica (PIVIC)”, who value and provide opportunities for all engagement and performance on this work as a research project, and that contribute to the state of this paper.

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Correspondence to Angel Rodrigues Ferreira .

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Rodrigues Ferreira, A., Carvalho Silva, A., Barreto Junior, C. (2021). Virtual Reconstruction of Objects by Point Cloud Capture to Measurement of Density Parameters Using Low Cost Device. In: Ruiz, P.H., Agredo-Delgado, V., Kawamoto, A.L.S. (eds) Human-Computer Interaction. HCI-COLLAB 2021. Communications in Computer and Information Science, vol 1478. Springer, Cham. https://doi.org/10.1007/978-3-030-92325-9_19

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  • DOI: https://doi.org/10.1007/978-3-030-92325-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92324-2

  • Online ISBN: 978-3-030-92325-9

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