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Photogrammetric 3D Reconstruction of Small Objects for a Real-Time Fruition

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Augmented Reality, Virtual Reality, and Computer Graphics (AVR 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12242))

Abstract

Among the techniques for digitalization and 3D modeling of real objects, photogrammetry is assuming an increasing importance due to easy procedures and low costs of hardware and software equipment. Thanks to the advances of the last years in computer vision, photogrammetry software can reconstruct the geometric 3D shape of an object from a series of pictures taken from different viewpoints. In particular, close-range photogrammetry for the reconstruction of small objects allows performing image acquisition around the target object almost automatically. In this paper we present a brief survey of the hardware setup, algorithms and software tools for photogrammetric acquisition and reconstruction applied to small objects, aimed at achieving a good photorealism level without an excessive computational load.

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Notes

  1. 1.

    https://www.heliconsoft.com/heliconsoft-products/helicon-focus/.

  2. 2.

    https://www.agisoft.com/pdf/metashape-pro_1_5_en.pdf.

  3. 3.

    https://colmap.github.io/tutorial.html.

  4. 4.

    https://www.capturingreality.com/.

  5. 5.

    https://www.3dflow.net/3df-zephyr-pro-3d-models-from-photos/.

  6. 6.

    https://www.autodesk.com/products/recap/overview.

  7. 7.

    http://ccwu.me/vsfm/.

  8. 8.

    https://www.regard3d.org/.

  9. 9.

    https://alicevision.org/.

  10. 10.

    https://www.opendronemap.org/.

  11. 11.

    https://devblogs.nvidia.com/introduction-nvidia-rtx-directx-ray-tracing/.

  12. 12.

    http://alice.loria.fr/index.php/software/3-platform/22-graphite.html.

  13. 13.

    https://www.atangeo.com/buy/nPro.

  14. 14.

    https://3dcoat.com/.

  15. 15.

    https://www.knaldtech.com/knald/.

  16. 16.

    https://www.gimp.org/.

References

  1. Barazzetti, L., Gianinetto, M., Scaioni, M.: Automatic processing of many images for 2D/3D modelling. In: Daniotti, B., Gianinetto, M., Della Torre, S. (eds.) Digital Transformation of the Design, Construction and Management Processes of the Built Environment. RD, pp. 355–365. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-33570-0_32

    Chapter  Google Scholar 

  2. Hanan, H., et al.: Batak Toba cultural heritage and close-range photogrammetry. Procedia - Soc. Behav. Sci. 184, 187–195 (2015)

    Article  Google Scholar 

  3. Fritsch, D., et al.: Modeling Façade structures using point clouds from dense image matching. In: International Conference on Advances in Civil, Structural and Mechanical Engineering, pp. 57–64 (2013)

    Google Scholar 

  4. Alidoost, F., Arefi, H.: An image-based technique for 3D building reconstruction using multi-view UAV images. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, vol. XL-1-W5, pp. 43–46. Copernicus GmbH. December 2015

    Google Scholar 

  5. Murtiyoso, A., Grussenmeyer, P.: Documentation of heritage buildings using close-range UAV images: dense matching issues, comparison and case studies. Photogram. Rec. 32(159), 206–229 (2017)

    Article  Google Scholar 

  6. Adamek, M., et al.: The possibilities of using drones in the 3D object modelling field. In: MATEC Web of Conferences, vol. 210 (2018)

    Google Scholar 

  7. Granshaw, S.I.: Structure from motion: origins and originality. Photogram. Rec. 33(161), 6–10 (2018)

    Article  Google Scholar 

  8. Girardi, F.: Rilevamento e modellazione tridimensionale per oggetti di piccole dimensioni. Ph.D. thesis, University of Bologna, May 2011

    Google Scholar 

  9. Bitelli, G.: Moderne tecniche e strumentazioni per il rilievo dei beni culturali. In: Atti della VI Conferenza Nazionale ASITA, Perugia, 5–8 Novembre (2002)

    Google Scholar 

  10. England, H.: Photogrammetric applications for cultural heritage. Guidance Good Pract. 8(2), 383–388 (2017)

    Google Scholar 

  11. Bitelli, G., et al.: The potential of 3D techniques for cultural heritage object documentation. In: Videometrics IX, vol. 6491, p. 64910S. International Society for Optics and Photonics, January 2007

    Google Scholar 

  12. Kaewrat, C., Boonbrahm, P.: Identify the object’s shape using augmented reality marker-based technique. Int. J. Adv. Sci. Eng. Inf. Technol. 9(6), 2193–2200 (2019)

    Article  Google Scholar 

  13. Phothong, W., et al.: Quality improvement of 3D models reconstructed from silhouettes of multiple images. Comput.-Aided Des. Appl. 15(3), 288–299 (2018)

    Article  Google Scholar 

  14. Remondino, F., et al.: Design and implement a reality-based 3D digitisation and modelling project. Dig. Heritage Int. Congr. 1, 137–144 (2013)

    Google Scholar 

  15. Gallo, A., et al.: 3D reconstruction of small sized objects from a sequence of multi-focused images. J. Cult. Heritage 15(2), 173–182 (2014)

    Article  MathSciNet  Google Scholar 

  16. Lastilla, L., et al.: 3D high-quality modeling of small and complex archaeological inscribed objects: rele vant issues and proposed methodology. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2-W11, pp. 699–706. Copernicus GmbH, May 2019

    Google Scholar 

  17. Clini, P., et al.: SFM technique and focus stacking for digital documentation of archaeological artifacts. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, vol. XLI-B5, pp. 229–236. Copernicus GmbH, June 2016

    Google Scholar 

  18. Kontogianni, G., et al.: Enhancing close-up image based 3D digitisation with focus stacking. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, vol. XLII-2-W5, pp. 421–425. Copernicus GmbH, August 2017

    Google Scholar 

  19. Galantucci, L.M., et al.: A stereo photogrammetry scanning methodology, for precise and accurate 3D digitization of small parts with sub-millimeter sized features. CIRP Ann. - Manuf. Technol. 64(1), 507–510 (2015)

    Article  Google Scholar 

  20. Sims-Waterhouse, D., et al.: Verification of micro-scale photogrammetry for smooth three-dimensional object measurement. Meas. Sci. Technol. 28(5), 055010 (2017)

    Article  Google Scholar 

  21. Galantucci, L.M., Guerra, M.G., Lavecchia, F.: Photogrammetry applied to small and micro scaled objects: a review. In: Ni, J., Majstorovic, V.D., Djurdjanovic, D. (eds.) AMP 2018. LNME, pp. 57–77. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-89563-5_4

    Chapter  Google Scholar 

  22. Lavecchia, F., et al.: Performance verification of a photogrammetric scanning system for micro-parts using a three-dimensional artifact: adjustment and calibration. Int. J. Adv. Manuf. Technol. 96(9), 4267–4279 (2018)

    Article  Google Scholar 

  23. Ritter, M., et al.: A landmark-based 3D calibration strategy for SPM. Meas. Sci. Technol. 18, 404–414 (2007)

    Article  Google Scholar 

  24. Barbieri, G., da Silva, F.P.: Acquisition of 3D models with submillimeter-sized features from SEM images by use of photogrammetry: a dimensional comparison to microtomography. Micron 121, 26–32 (2019)

    Article  Google Scholar 

  25. Marshall, M.E., et al.: Automatic photogrammetry for the 3D digitisation of small artefact collections. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, pp. 355–365. Research for Development (2019)

    Google Scholar 

  26. Schönberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016)

    Google Scholar 

  27. Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)

    Article  MathSciNet  Google Scholar 

  28. Schönberger, J.L., Zheng, E., Frahm, J.-M., Pollefeys, M.: Pixelwise view selection for unstructured multi-view stereo. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9907, pp. 501–518. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46487-9_31

    Chapter  Google Scholar 

  29. Bocanet, V., et al.: Low-cost industrial photogrammetry for rapid prototyping. In: MATEC Web of Conferences, vol. 137, p. 06001 (2017)

    Google Scholar 

  30. Reljić, I., et al.: Photogrammetric 3D scanning of physical objects: tools and workflow. TEM J. 8(2), 383–388 (2019)

    Google Scholar 

  31. Palestini, C., Basso, A.: The photogrammetric survey methodologies applied to low cost 3D virtual exploration in multidisciplinary field. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. vol. XLII-2-W8, pp. 195–202. Copernicus GmbH, November 2017

    Google Scholar 

  32. Vacca, G.: Overview of open source software for close range photogrammetry. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, vol. XLII-4-W14, pp. 239–245. Copernicus GmbH, August 2019

    Google Scholar 

  33. Le, B.H., et al.: High-quality object-space dynamic ambient occlusion for characters using bi-level regression. In: I3D 2019: ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, I3D 2019, pp. 1–10. Association for Computing Machinery, May 2019

    Google Scholar 

  34. Campagnolo, L.Q., Celes, W.: Interactive directional ambient occlusion and shadow computations for volume ray casting. Comput. Graph. (Pergamon) 84, 66–76 (2019)

    Article  Google Scholar 

  35. Verhoeven, G.J.: Computer graphics meets image fusion: the power of texture baking to simultaneously visualise 3D surface features and colour. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. IV-2-W2, pp. 295–302. Copernicus GmbH, August 2017

    Google Scholar 

  36. Yin, Y., et al.: Texture mapping based on photogrammetric reconstruction of the coded markers. Appl. Opt. 58(5), A48–A54 (2019)

    Article  Google Scholar 

  37. Wang, T.C., et al.: SVBRDF-invariant shape and reflectance estimation from a light-field camera. IEEE Trans. Pattern Anal. Mach. Intell. 40(3), 740–754 (2018)

    Article  Google Scholar 

  38. Innmann, M., et al.: BRDF-reconstruction in photogrammetry studio setups. In: IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 3346–3354, March 2020

    Google Scholar 

  39. Ono, T., et al.: Practical BRDF reconstruction using reliable geometric regions from multi-view stereo. Comput. Vis. Media 5(4), 325–336 (2019)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Engineering for Innovation, University of Salento, Lecce, Italy

    Lucio Tommaso De Paolis, Valerio De Luca, Giovanni D’Errico & Giovanna Ilenia Paladini

  2. Department of Cultural Heritage, University of Salento, Lecce, Italy

    Carola Gatto

Authors
  1. Lucio Tommaso De Paolis
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  2. Valerio De Luca
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  3. Carola Gatto
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  4. Giovanni D’Errico
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  5. Giovanna Ilenia Paladini
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Contributions

The author Carola Gatto wrote Sect. 2 of the paper, entitled “Photogrammetry for cultural heritage”.

Corresponding author

Correspondence to Valerio De Luca .

Editor information

Editors and Affiliations

  1. University of Salento, Lecce, Italy

    Lucio Tommaso De Paolis

  2. University of Paris-Sud, Orsay, France

    Patrick Bourdot

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De Paolis, L.T., De Luca, V., Gatto, C., D’Errico, G., Paladini, G.I. (2020). Photogrammetric 3D Reconstruction of Small Objects for a Real-Time Fruition. In: De Paolis, L., Bourdot, P. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2020. Lecture Notes in Computer Science(), vol 12242. Springer, Cham. https://doi.org/10.1007/978-3-030-58465-8_28

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  • DOI: https://doi.org/10.1007/978-3-030-58465-8_28

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