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Link to original content: https://doi.org/10.1007/978-3-031-31438-4_32
The Multi-view Geometry of Parallel Cylinders | SpringerLink
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The Multi-view Geometry of Parallel Cylinders

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Image Analysis (SCIA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13886))

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Abstract

In this paper we study structure from motion problems for parallel cylinders. Using sparse keypoint correspondences is an efficient (and standard) way to solve the structure from motion problem. However, point features are sometimes unavailable and they can be unstable over time and viewing conditions. Instead, we propose a framework based on silhouettes of quadric surfaces, with special emphasis on parallel cylinders. Such structures are quite common, e.g. trees, lampposts, pillars, and furniture legs. Traditionally, the projection of the center lines of such cylinders have been considered and used in computer vision. Here, we demonstrate that the apparent width of the cylinders also contains useful information for structure and motion estimation. We provide mathematical analysis of relative structure and relative motion tensors, which is used to develop a number of minimal solvers for simultaneously estimating camera pose and scene structure from silhouette lines of cylinders. These solvers can be used efficiently in robust estimation schemes, such as RANSAC. We use Sampson-approximation methods for efficient estimation using over-determined data and develop averaging techniques. We also perform synthetic accuracy and robustness tests and evaluate our methods on a number of real-world scenarios.

This work was supported by the ADACORSA project with funding from ECSEL JU in the H2020 Framework Programme (H2020/2014-2020) and National Authorities, under GA 876019, the strategic research projects ELLIIT, the Swedish Foundation for Strategic Research project, Semantic Mapping and Visual Navigation for Smart Robots (grant no. RIT15-0038) and by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation.

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References

  1. Akinlar, C., Topal, C.: EDlines: real-time line segment detection by edge drawing (ed). In: Proceedings of International Conference on Image Processing (ICIP), pp. 2837–2840 (2011). https://doi.org/10.1109/ICIP.2011.6116138

  2. Åström, K., Oskarsson, M.: Solutions and ambiguities of the structure and motion problem for 1D retinal vision. J. Math. Imaging Vis. 12(2), 121–135 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  3. Åström, K.: Invariancy Methods for Points, Curves and Surfaces in Computational Vision. Ph.D. thesis, Lund Unicersiry (1996)

    Google Scholar 

  4. Åström, K.: Using combinations of points, lines and conics to estimate structure and motion. In: Proceedings of Symposium on Image Analysis, pp. 61–64. SSBA (1998)

    Google Scholar 

  5. Åström, K., Cipolla, R., Giblin, P.J.: Generalised epipolar constraints. Int. J. Comput. Vis. 33, 51–72 (1999)

    Article  Google Scholar 

  6. Åström, K., Kahl, F.: Motion estimation in image sequences using the deformation of apparent contours. IEEE Trans. Pattern Anal. Mach. Intell. 21(2), 114–127 (1999)

    Article  Google Scholar 

  7. Åström, K., Kahl, F., Heyden, A., Berthilsson, R.: A statistical approach to structure and motion from image features. In: Amin, A., Dori, D., Pudil, P., Freeman, H. (eds.) SSPR /SPR 1998. LNCS, vol. 1451, pp. 929–936. Springer, Heidelberg (1998). https://doi.org/10.1007/BFb0033321

    Chapter  Google Scholar 

  8. Barath, D., Polic, M., Förstner, W., Sattler, T., Pajdla, T., Kukelova, Z.: Making affine correspondences work in camera geometry computation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12356, pp. 723–740. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58621-8_42

    Chapter  Google Scholar 

  9. Cho, N.G., Yuille, A., Lee, S.W.: A novel linelet-based representation for line segment detection. IEEE Trans. Pattern Anal. Mach. Intell. 40(5), 1195–1208 (2018). https://doi.org/10.1109/TPAMI.2017.2703841

    Article  Google Scholar 

  10. De Ma, S.: Conics-based stereo, motion estimation, and pose determination. Int. J. Comput. Vis. 10(1), 7–25 (1993)

    Article  Google Scholar 

  11. Frosio, I., Alzati, A., Bertolini, M., Turrini, C., Borghese, N.A.: Linear pose estimate from corresponding conics. Pattern Recogn. 45(12), 4169–4181 (2012)

    Article  Google Scholar 

  12. Frosio, I., Turrini, C., Alzati, A.: Camera re-calibration after zooming based on sets of conics. Vis. Comput. 32(5), 663–674 (2016)

    Article  Google Scholar 

  13. Gillsjö, D., Flood, G., Åström, K.: Semantic room wireframe detection from a single view. In: Proceedings of International Conference on Pattern Recognition (ICPR), pp. 1886–1893. IEEE (2022). https://doi.org/10.1109/ICPR56361.2022.9956252

  14. Grompone von Gioi, R., Jakubowicz, J., Morel, J.M., Randall, G.: LSD: a fast line segment detector with a false detection control. IEEE Trans. Pattern Anal. Mach. Intell. 32(4), 722–732 (2010). https://doi.org/10.1109/TPAMI.2008.300

  15. Gu, G., Ko, B., Go, S., Lee, S.H., Lee, J., Shin, M.: Towards light-weight and real-time line segment detection. In: Proceedings of Conference on Artificial Intelligence (AAAI), pp. 726–734 (2022)

    Google Scholar 

  16. Gummeson, A., Engman, J., Åström, K., Oskarsson, M.: Fast and efficient minimal solvers for quadric based camera pose estimation. In: Proceedings of International Conference on Pattern Recognition (ICPR), pp. 3973–3979. IEEE (2022)

    Google Scholar 

  17. Gummeson, A., Oskarsson, M.: Robust and accurate cylinder triangulation. In: Proceedings of Scandinavian Conference on Image Analysis (SCIA). Springer (2023)

    Google Scholar 

  18. Hanek, R., Navab, N., Appel, M.: Yet another method for pose estimation: a probabilistic approach using points, lines, and cylinders. In: Proceedings of Computer Society Conference on Computer Vision and Pattern Recognition (CVPR). vol. 2, pp. 544–550. IEEE (1999)

    Google Scholar 

  19. Huang, K., Wang, Y., Zhou, Z., Ding, T., Gao, S., Ma, Y.: Learning to parse wireframes in images of man-made environments. In: Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), pp. 626–635. IEEE (2018)

    Google Scholar 

  20. Kahl, F., Heyden, A.: Structure and motion from points, lines and conics with affine cameras. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1406, pp. 327–341. Springer, Heidelberg (1998). https://doi.org/10.1007/BFb0055676

    Chapter  Google Scholar 

  21. Kahl, F., Heyden, A.: Using conic correspondences in two images to estimate the epipolar geometry. In: Proceedings of International Conference on Computer Vision (ICCV), pp. 761–766. IEEE (1998)

    Google Scholar 

  22. Kaminski, J., Shashua, A.: Multiple view geometry of algebraic curves. Int. J. Comput. Vis. 56(3), 195–219 (2003)

    Google Scholar 

  23. Kuang, Y., Åström, K.: Pose estimation with unknown focal length using points, directions and lines. In: Proceedings of International Conference on Computer Vision (ICCV), pp. 529–536. IEEE (2013)

    Google Scholar 

  24. Kuang, Y., Burgess, S., Torstensson, A., Åström, K.: A complete characterization and solution to the microphone position self-calibration problem. In: Proceedings of of International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3875–3879. IEEE (2013)

    Google Scholar 

  25. Larsson, V., Åstrom, K., Oskarsson, M.: Efficient solvers for minimal problems by syzygy-based reduction. In: Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), pp. 820–829. IEEE (2017)

    Google Scholar 

  26. Liu, C., Hu, W.: Real-time geometric fitting and pose estimation for surface of revolution. Pattern Recogn. 85, 90–108 (2019)

    Article  Google Scholar 

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

    Article  Google Scholar 

  28. Ma, S., Li, L.: Ellipsoid reconstruction from three perspective views. In: Proceedings of International Conference on Pattern Recognition (ICPR). vol. 1, pp. 344–348. IEEE (1996)

    Google Scholar 

  29. Mei, J., Zhang, D., Ding, Y.: Monocular vision for pose estimation in space based on cone projection. Opt. Eng. 56(10), 103108 (2017)

    Article  Google Scholar 

  30. Mudigonda, P.K., Jawahar, C., Narayanan, P.: Geometric structure computation from conics. In: Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), pp. 9–14. Citeseer (2004)

    Google Scholar 

  31. Mur-Artal, R., Montiel, J.M.M., Tardos, J.D.: ORB-SLAM: a versatile and accurate monocular SLAM system. IEEE Trans. Robot. 31(5), 1147–1163 (2015)

    Article  Google Scholar 

  32. Navab, N., Appel, M.: Canonical representation and multi-view geometry of cylinders. Int. J. Comput. Vis. 70(2), 133–149 (2006)

    Article  Google Scholar 

  33. Oskarsson, M., Åström, K.: Accurate and automatic surveying of beacon positions for a laser guided vehicle. In: Proceedings of European Consortium for Mathematics in Industry (ECMI) (1998)

    Google Scholar 

  34. Oskarsson, M., Åström, K., Overgaard, N.C.: Minimal cases of the structure and motion problem with missing data for one-dimensional retinae. In: Proceedings of Scandinavian Conference on Image Analysis (SCIA), pp. 482–489. Springer (2001)

    Google Scholar 

  35. Oskarsson, M., Åström, K., Overgaard, N.C.: The minimal structure and motion problems with missing data for 1D retina vision. J. Math. Imaging Vis. 26(3), 327–343 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  36. Pautrat, R., Lin, J.T., Larsson, V., Oswald, M.R., Pollefeys, M.: SOLD2: self-supervised occlusion-aware line description and detection. In: Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), pp. 11368–11378. IEEE (2021)

    Google Scholar 

  37. Quan, L.: Invariant of a pair of non-coplanar conics in space: Definition, geometric interpretation and computation. In: Proceedings of International Conference on Computer Vision, pp. 926–931. IEEE (1995)

    Google Scholar 

  38. Quan, L.: Conic reconstruction and correspondence from two views. IEEE Trans. Pattern Anal. Mach. Intell. 18(2), 151–160 (1996)

    Article  MathSciNet  Google Scholar 

  39. Quan, L.: Uncalibrated 1D projective camera and 3D affine reconstruction of lines. In: Proceedings of Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 60–65. IEEE (1997)

    Google Scholar 

  40. Raposo, C., Barreto, J.P.: Theory and practice of structure-from-motion using affine correspondences. In: Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5470–5478. IEEE (2016)

    Google Scholar 

  41. Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to SIFT or SURF. In: Proceedings of International conference on computer vision (ICCV), pp. 2564–2571. IEEE (2011)

    Google Scholar 

  42. Sattler, T., et al.: Benchmarking 6dof outdoor visual localization in changing conditions. In: Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8601–8610. IEEE (2018)

    Google Scholar 

  43. Schönberger, J.L., Frahm, J.M.: Structure-from-motion revisited. In: Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4104–4113. IEEE (2016)

    Google Scholar 

  44. 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 

  45. Stewénius, H.: Gröbner Basis Methods for Minimal Problems in Computer Vision. Ph.D. thesis, Lund University (2005)

    Google Scholar 

  46. Triggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W.: Bundle adjustment — a modern synthesis. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) IWVA 1999. LNCS, vol. 1883, pp. 298–372. Springer, Heidelberg (2000). https://doi.org/10.1007/3-540-44480-7_21

    Chapter  Google Scholar 

  47. Xu, Y., Xu, W., Cheung, D., Tu, Z.: Line segment detection using transformers without edges. In: Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4257–4266. IEEE (2021)

    Google Scholar 

  48. Xue, N., et al.: Learning regional attraction for line segment detection. IEEE Trans. Pattern Anal. Mach. Intell. 43(6), 1998–2013 (2019)

    Article  Google Scholar 

  49. Xue, N., et al.: Holistically-attracted wireframe parsing. In: Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2788–2797. IEEE (2020)

    Google Scholar 

  50. Zheng, J., Zhang, J., Li, J., Tang, R., Gao, S., Zhou, Z.: Structured3D: a large photo-realistic dataset for structured 3D modeling. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12354, pp. 519–535. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58545-7_30

    Chapter  Google Scholar 

  51. Zhou, Y., Qi, H., Ma, Y.: End-to-end wireframe parsing. In: Proceedings of International Conference on Computer Vision, pp. 962–971. IEEE (2019)

    Google Scholar 

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Tegler, E. et al. (2023). The Multi-view Geometry of Parallel Cylinders. In: Gade, R., Felsberg, M., Kämäräinen, JK. (eds) Image Analysis. SCIA 2023. Lecture Notes in Computer Science, vol 13886. Springer, Cham. https://doi.org/10.1007/978-3-031-31438-4_32

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