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3D reconstruction system based on incremental structure from motion using a camera with varying parameters

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Abstract

In this paper, we present a flexible and fast system for multi-scale objects/scenes 3D reconstruction from uncalibrated images/video taken by a moving camera characterized by variable parameters. The proposed system is based on incremental structure from motion and good exploitation of bundle adjustment. At first, from two selected images, our system allows to recover, in a well-chosen reference, coordinates of a set of 3D points. In this context, we have proposed a new method of self-calibration based on the use of two unknown scene points with their image projections. After that, new images are inserted progressively using 3D information already obtained. Local bundle adjustment is used to adjust the new estimated entities. At some time, we introduce a global bundle adjustment to adjust as best as possible all estimated entities and to have an initial 3D model of quality covering an interesting part of the object/scene. This model will be used as reference for the insertion of the rest of images. The proposed system allows to obtain satisfactory results within a reasonable time.

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References

  1. El Hazzat, S., Saaidi, A., Karam, A., Satori, K.: Incremental multi-view 3D reconstruction starting from two images taken by a stereo pair of cameras. 3D Res. 6, 11 (2015). doi:10.1007/s13319-015-0041-z

    Article  Google Scholar 

  2. Lhuillier, M., Quan, L.: A quasi-dense approach to surface reconstruction from uncalibrated images. IEEE Trans. Pattern Anal. Mach. Intell. 27(3), 418–433 (2005)

    Article  Google Scholar 

  3. Wong, S.S., Chan, K.L.: 3D object model reconstruction from image sequence based on photometric consistency in volume space. Pattern Anal. Appl. 13(4), 437–450 (2009)

    Article  MathSciNet  Google Scholar 

  4. Ding, L., Ding, X., Fang, C.: 3D face sparse reconstruction based on local linear fitting. Vis. Comput. 30(2), 189–200 (2014)

    Article  Google Scholar 

  5. Pollefeys, M., Gool, L.V., Vergauwen, M., Verbiest, F., Cornelis, K., Tops, J., Koch, R.: Visual modeling with a hand-held camera. Int. J. Comput. Vis. 59(3), 207–232 (2004)

    Article  Google Scholar 

  6. Merras, M., El Hazzat, S., Saaidi, A., Satori, K., Nazih, A.: 3D face reconstruction using images from cameras with varying parameters. Int. J. Autom. Comput. (2016). doi:10.1007/s11633-016-0999-x

  7. Liu, J., Li, C., Mei, F., Wang, Z.: 3D entity-based stereo matching with ground control points and joint second order smoothness prior. Vis. Comput. 31(9), 1253–1269 (2015)

    Article  Google Scholar 

  8. Tola, E., Strecha, C., Fua, P.: Efficient large-scale multi-view stereo for ultra high-resolution image sets. Mach. Vis. Appl. 23(5), 903–920 (2012)

    Article  Google Scholar 

  9. Vu, H.H., Labatut, P., Pons, J.P., Keriven, R.: High accuracy and visibility-consistent dense multiview stereo. IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 889–901 (2012)

    Article  Google Scholar 

  10. Furukawa, Y., Ponce, J.: Accurate, dense, and robust multiview stereopsis. IEEE Trans. Pattern Anal. Mach. Intell. 32(8), 1362–1376 (2010)

    Article  Google Scholar 

  11. Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: exploring photo collections in 3D. In: SIGGRAPH Conference Proceedings, pp. 835–846 (2006)

  12. Mouragnon, E., Lhuillier, M., Dhome, M., Dekeyser, F., Sayd, P.: Generic and real-time structure from motion using local bundle adjustment. Image Vis. Comput. 27(8), 1178–1193 (2009)

    Article  Google Scholar 

  13. Fuhrmann, S., Langguth, F., Moehrle, N., Waechter, M., Goesele, M.: MVE—an image-based reconstruction environment. Comput. Gr. 53, 44–53 (2015). Part A

    Article  Google Scholar 

  14. El Akkad, N., El Hazzat, S., Saaidi, A., Satori, K.: Reconstruction of 3D scenes by camera self-calibration and using genetic algorithms. 3D Res. 7, 6 (2016). 10.1007/s13319-016-0082-y

    Article  Google Scholar 

  15. Wang, G., Wu, Q.M.J.: Perspective 3-D Euclidean reconstruction with varying camera parameters. IEEE Trans. Circuits Syst. Video Technol. 19(12), 1793–1803 (2009)

    Article  Google Scholar 

  16. Strecha, C., Tuytelaars, T., Van Gool, L.: Dense matching of multiple wide-baseline views. In: Proceedings of the International Conference on Computer Vision, pp. 1194–1201 (2003)

  17. Amenta, N., Bern, M., Kamvysselis, M.: A new Voronoi-based surface reconstruction algorithm. In: Proceedings of SIGGRAPH’98, pp. 415–421 (1998)

  18. Kazhdan, M., Bolithp, M., Hoppe, H.: Poisson surface reconstruction. In: Proceedings of Eurographics Symposium on Geometry Processing, pp. 61–70 (2006)

  19. Lim, H., Lim, J., Kim, H. J.: Real-time 6-DOF monocular visual SLAM in a large-scale environment. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 1532–1539 (2014)

  20. Kerl, C., Sturm, J., Cremers, D.: Dense visual slam for RGB-D cameras. In: International Conference on Intelligent Robots and Systems (IROS), pp. 2100–2106 (2013)

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

    Article  Google Scholar 

  22. Wu, C., Agarwal, S., Curless, B., Seitz. S. M.: Multicore bundle adjustment. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3057–3064 (2011)

  23. Lourakis, M.A., Argyros, A.: SBA: a software package for generic sparse bundle adjustment. ACM Trans. Math. Softw. 36(1), 1–30 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  24. Brown, M., Lowe, D. G.: Unsupervised 3D object recognition and reconstruction in unordered datasets. In: Proceedings of the International Conference on 3D Digital Imaging and Modelling, pp. 56–63 (2005)

  25. Tran, S., Davis, L.: 3D surface reconstruction using graph cuts with surface constraints. In: Proceedings of the European Conference on Computer Vision, pp. 219–231 (2006)

  26. Snavely, N., Seitz, S., Szeliski, R.: Modeling the world from internet photo collections. Int. J. Comput. Vis. 80(2), 189–210 (2008)

    Article  Google Scholar 

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

  28. Wu, C.: Critical configurations for radial distortion self-calibration. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 25–32 (2014)

  29. Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)

    Article  Google Scholar 

  30. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)

    Article  Google Scholar 

  31. Wu, J., Cui, Z., Sheng, V.S., Zhao, P., Su, D., Gong, S.: A comparative study of sift and its variants. Meas. Sci. Rev. 13(3), 122–131 (2013)

    Article  Google Scholar 

  32. Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004)

    Book  MATH  Google Scholar 

  33. Moré, J.J.: The Levenberg–Marquardt algorithm: implementation and theory. In: Watson, G.A. (ed.) Numerical Analysis, Lecture Notes in Mathematics, vol. 630, pp. 105–116. Springer, Berlin (1977)

    Google Scholar 

  34. http://www.cs.unc.edu/~marc/research.html

  35. Strecha, C., Von Hansen, W., Van Gool, L., Fua, P., Thoennessen, U.: On benchmarking camera calibration and multi-view stereo for high resolution imagery. In: CVPR, pp. 1–8 (2008)

  36. Lhuillier, M., Quan, L.: Match propagation for image-based modeling and rendering. IEEE Trans. Pattern Anal. Mach. Intell. 24(8), 1140–1146 (2002)

    Article  Google Scholar 

  37. Wu, C.: Towards linear-time incremental structure from motion. In: International Conference on 3D Vision (3DV), pp. 127–134 (2013)

  38. http://ccwu.me/vsfm/

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Authors and Affiliations

  1. LIIAN, Department of Mathematics and Informatics, Faculty of Sciences Dhar-Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Soulaiman El Hazzat, Mostafa Merras, Nabil El Akkad, Abderrahim Saaidi & Khalid Satori

  2. LSI, Department of Mathematics, Physics and Informatics, Polydisciplinary Faculty of Taza, Sidi Mohamed Ben Abdellah University, Taza, Morocco

    Abderrahim Saaidi

  3. Department of Mathematics and Computer Science, National School of Applied Sciences (ENSA) of Al-Hoceima, Mohamed First University, Oujda, Morocco

    Nabil El Akkad

Authors
  1. Soulaiman El Hazzat
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  2. Mostafa Merras
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  3. Nabil El Akkad
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  4. Abderrahim Saaidi
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  5. Khalid Satori
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Correspondence to Soulaiman El Hazzat.

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El Hazzat, S., Merras, M., El Akkad, N. et al. 3D reconstruction system based on incremental structure from motion using a camera with varying parameters. Vis Comput 34, 1443–1460 (2018). https://doi.org/10.1007/s00371-017-1451-0

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