Skip to main content
SpringerLink
Log in

Adaptive Structure from Motion with a Contrario Model Estimation

  • Conference paper
Computer Vision – ACCV 2012 (ACCV 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7727))

Included in the following conference series:

Abstract

Structure from Motion (SfM) algorithms take as input multi-view stereo images (along with internal calibration information) and yield a 3D point cloud and camera orientations/poses in a common 3D coordinate system. In the case of an incremental SfM pipeline, the process requires repeated model estimations based on detected feature points: homography, fundamental and essential matrices, as well as camera poses. These estimations have a crucial impact on the quality of 3D reconstruction. We propose to improve these estimations using the a contrario methodology. While SfM pipelines usually have globally-fixed thresholds for model estimation, the a contrario principle adapts thresholds to the input data and for each model estimation. Our experiments show that adaptive thresholds reach a significantly better precision. Additionally, the user is free from having to guess thresholds or to optimistically rely on default values. There are also cases where a globally-fixed threshold policy, whatever the threshold value is, cannot provide the best accuracy, contrary to an adaptive threshold policy.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Agarwal, S., Snavely, N., Simon, I., Seitz, S., Szeliski, R.: Building Rome in a day. In: 12th IEEE International Conference on Computer Vision (ICCV), pp. 72–79 (2009)

    Google Scholar 

  2. Frahm, J.-M., Fite-Georgel, P., Gallup, D., Johnson, T., Raguram, R., Wu, C., Jen, Y.-H., Dunn, E., Clipp, B., Lazebnik, S., Pollefeys, M.: Building Rome on a Cloudless Day. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 368–381. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  3. Kahl, F.: Multiple view geometry and the L  ∞ -norm. In: ICCV, pp. 1002–1009 (2005)

    Google Scholar 

  4. Dalalyan, A., Keriven, R.: L 1-penalized robust estimation for a class of inverse problems arising in multiview geometry. In: NIPS, pp. 441–449 (2009)

    Google Scholar 

  5. Furukawa, Y., Ponce, J.: Accurate, dense, and robust multiview stereopsis. IEEE Transactions on Pattern Analysis and Machine Intelligence 32, 1362–1376 (2010)

    Article  Google Scholar 

  6. Hiep, V., Keriven, R., Labatut, P., Pons, J.: Towards high-resolution large-scale multi-view stereo. In: CVPR, pp. 1430–1437 (2009)

    Google Scholar 

  7. Zach, C., Klopschitz, M., Pollefeys, M.: Disambiguating visual relations using loop constraints. In: CVPR, pp. 1426–1433 (2010)

    Google Scholar 

  8. Aanæs, H., Dahl, A., Steenstrup Pedersen, K.: Interesting interest points. International Journal of Computer Vision 97, 18–35 (2012)

    Article  Google Scholar 

  9. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision (IJCV) 60, 91–110 (2004)

    Article  Google Scholar 

  10. Bay, H., Tuytelaars, T., Van Gool, L.: SURF: Speeded Up Robust Features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  11. Lourakis, M.I.A., Argyros, A.A.: SBA: A software package for generic sparse bundle adjustment. ACM Transactions on Mathematical Software (TOMS) 36 (2009)

    Google Scholar 

  12. Wu, C., Agarwal, S., Curless, B., Seitz, S.M.: Multicore bundle adjustment. In: CVPR, pp. 3057–3064 (2011)

    Google Scholar 

  13. Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: exploring photo collections in 3D. ACM Transactions on Graphics (TOG) 25, 835–846 (2006)

    Article  Google Scholar 

  14. Gherardi, R., Farenzena, M., Fusiello, A.: Improving the efficiency of hierarchical structure-and-motion. In: CVPR, pp. 1594–1600 (2010)

    Google Scholar 

  15. Havlena, M., Torii, A., Knopp, J., Pajdla, T.: Randomized structure from motion based on atomic 3D models from camera triplets. In: CVPR, pp. 2874–2881 (2009)

    Google Scholar 

  16. Scaramuzza, D., Fraundorfer, F.: Visual odometry: Part I - the first 30 years and fundamentals. IEEE Robot. Automat. Mag. 18 (2011)

    Google Scholar 

  17. Fraundorfer, F., Scaramuzza, D.: Visual odometry: Part II - matching, robustness, and applications. IEEE Robot. Automat. Mag. 19 (2012)

    Google Scholar 

  18. Martinec, D., Pajdla, T.: Robust rotation and translation estimation in multiview reconstruction. In: CVPR (2007)

    Google Scholar 

  19. Govindu, V.M.: Combining two-view constraints for motion estimation. In: CVPR, vol. 2, pp. II.218–II.225 (2001)

    Google Scholar 

  20. Govindu, V.M.: Robustness in Motion Averaging. In: Narayanan, P.J., Nayar, S.K., Shum, H.-Y. (eds.) ACCV 2006. LNCS, vol. 3852, pp. 457–466. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  22. Desolneux, A., Moisan, L., Morel, J.M.: From Gestalt theory to image analysis: a probabilistic approach, 1st edn. Springer (2007)

    Google Scholar 

  23. Moisan, L., Moulon, P., Monasse, P.: Automatic homographic registration of a pair of images, with a contrario elimination of outliers. Image Processing On Line (2012), http://dx.doi.org/10.5201/ipol.2012.mmm-oh

  24. Moisan, L., Stival, B.: A probabilistic criterion to detect rigid point matches between two images and estimate the fundamental matrix. Int. J. of Computer Vision (IJCV) 57, 201–218 (2004)

    Article  Google Scholar 

  25. Rabin, J., Delon, J., Gousseau, Y., Moisan, L.: MAC-RANSAC: a robust algorithm for the recognition of multiple objects. In: Proc. of 3DPTV 2010, Paris (2010)

    Google Scholar 

  26. Nistér, D.: An efficient solution to the five-point relative pose problem. In: CVPR, vol. 2, pp. II.195–II.202 (2003)

    Google Scholar 

  27. Lepetit, V., Moreno-Noguer, F., Fua, P.: EPnP: an accurate O(n) solution to the PnP problem. International Journal of Computer Vision (IJCV) 81, 155–166 (2009)

    Article  Google Scholar 

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

    Google Scholar 

  29. Haralick, R.M., Shapiro, L.G.: Computer and Robot Vision, 1st edn. Addison-Wesley Longman Publishing Co., Inc., Boston (1992)

    Google Scholar 

  30. Rabin, J., Delon, J., Gousseau, Y.: A statistical approach to the matching of local features. SIAM J. Imaging Sciences 2, 931–958 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  31. Sabater, N., Almansa, A., Morel, J.M.: Meaningful matches in stereovision. IEEE Transactions on Pattern Analysis and Machine Intelligence 99 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. LIGM (UMR CNRS), Center for Visual Computing, ENPC, Université Paris-Est, 6-8 av. Blaise Pascal, 77455, Marne-la-Vallée, France

    Pierre Moulon, Pascal Monasse & Renaud Marlet

  2. Mikros Image., 120 rue Danton, 92300, Levallois-Perret, France

    Pierre Moulon

Authors
  1. Pierre Moulon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pascal Monasse
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Renaud Marlet
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, 151-744, Seoul, Korea

    Kyoung Mu Lee

  2. Microsoft Research Asia, No. 5, Danling st., Haidian district, 100080, Beijing, P.R. China

    Yasuyuki Matsushita

  3. School of Interactive Computing, Georgia Institute of Technology, 801 Atlantic Drive, CCB 315, 30332, Atlanta, GA, USA

    James M. Rehg

  4. Institute of Automation, National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Zhong Quan Cun East Road 95, Haidian District,, 100 190, Beijing, P.R. China

    Zhanyi Hu

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Moulon, P., Monasse, P., Marlet, R. (2013). Adaptive Structure from Motion with a Contrario Model Estimation. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7727. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37447-0_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37447-0_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37446-3

  • Online ISBN: 978-3-642-37447-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation