Skip to main content
SpringerLink
Log in
Book cover

Methods for Appearance-based Loop Closure Detection pp 99–118Cite as

Loop Closure Detection Using Incremental Bags of Binary Words

  • Chapter
  • First Online:

  • 678 Accesses

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 122))

Abstract

This chapter introduces a novel method for computing a visual vocabulary online. This binary vocabulary, in combination with an inverted file, conforms an index of images called OBIndex (Online Binary Image Index), which can be used to efficiently retrieve previously seen places. This chapter also presents a topological mapping algorithm called BINMap (Binary Mapping), which makes use of OBIndex as a key component to obtain loop closure candidates during the likelihood computation.

This is a preview of subscription content, 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   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

Notes

  1. 1.

    http://github.com/emiliofidalgo/obindex.

References

  1. Cummins, M., Newman, P.: FAB-MAP: probabilistic localization and mapping in the space of appearance. Int. J. Robot. Res. 27(6), 647–665 (2008)

    Google Scholar 

  2. Angeli, A., Filliat, D., Doncieux, S., Meyer, J.A.: A fast and incremental method for loop-closure detection using bags of visual words. IEEE Trans. Robot. 24(5), 1027–1037 (2008)

    Google Scholar 

  3. Fraundorfer, F., Engels, C., Nister, D.: Topological mapping, localization and navigation using image collections. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3872–3877 (2007)

    Google Scholar 

  4. Galvez-Lopez, D., Tardos, J.: Real-Time loop detection with bags of binary words. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 51–58 (2011)

    Google Scholar 

  5. Sivic, J., Zisserman, A.: Video google: a text retrieval approach to object matching in videos. In: IEEE International Conference on Computer Vision, pp. 1470–1477 (2003)

    Google Scholar 

  6. Nister, D., Stewenius, H.: Scalable recognition with a vocabulary tree. IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 2161–2168 (2006)

    Google Scholar 

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

    Google Scholar 

  8. Bay, H., Tuytelaars, T., Van Gool, L.: SURF: speeded up robust features. In: European Conference on Computer Vision, Lecture Notes in Computer Science, vol. 3951, pp. 404–417 (2006)

    Google Scholar 

  9. Calonder, M., Lepetit, V., Strecha, C., Fua, P.: BRIEF : binary robust independent elementary features. In: European Conference on Computer Vision, Lecture Notes in Computer Science, vol. 6314, pp. 778–792 (2010)

    Google Scholar 

  10. Leutenegger, S., Chli, M., Siegwart, R.: Brisk: binary robust invariant scalable keypoints. In: IEEE International Conference on Computer Vision, pp. 2548–2555 (2011)

    Google Scholar 

  11. Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to SIFT or SURF. IEEE International Conference on Computer Vision, vol. 95, pp. 2564–2571 (2011)

    Google Scholar 

  12. Alahi, A., Ortiz, R., Vandergheynst, P.: FREAK : fast retina keypoint. In: IEEE Conference on Computer Vision Pattern Recognition, pp. 510–517 (2012)

    Google Scholar 

  13. Yang, X., Cheng, K.T.: Local difference binary for ultrafast and distinctive feature description. IEEE Trans. Pattern Anal. Mach. Intell. 36(1), 188–94 (2014)

    Google Scholar 

  14. Galvez-Lopez, D., Tardos, J.: Bags of binary words for fast place recognition in image sequences. IEEE Trans. Robot. 28(5), 1188–1197 (2012)

    Google Scholar 

  15. Khan, S., Wollherr, D.: IBuILD: incremental bag of binary words for appearance-based loop closure detection. In: IEEE International Conference on Robotics and Automation, pp. 5441–5447 (2015)

    Google Scholar 

  16. Garcia-Fidalgo, E., Ortiz, A.: On the use of binary feature descriptors for loop closure detection. In: IEEE Emerging Technologies and Factory Automation, pp. 1–8 (2014)

    Google Scholar 

  17. Gionis, A., Indyk, P., Motwani, R.: Similarity search in high dimensions via hashing. In: International Conference on Very Large Data Bases, pp. 518–529 (1999)

    Google Scholar 

  18. Salakhutdinov, R., Hinton, G.: Semantic hashing. Int. J. Approx. Reason. 50(7), 969–978 (2009)

    Google Scholar 

  19. Muja, M., Lowe, D.G.: Fast matching of binary features. In: Conference on Computer and Robot Vision, pp. 404–410 (2012)

    Google Scholar 

  20. Sparck Jones, K.: A statistical interpretation of term specificity and its application in retrieval. J. Doc. 28, 11–21 (1972)

    Google Scholar 

  21. Rosten, E., Drummond, T.: Machine learning for high-speed corner detection. In: European Conference on Computer Vision, pp. 430–443 (2006)

    Google Scholar 

  22. Cummins, M., Newman, P.: Appearance-only SLAM at large scale with FAB-MAP 2.0. Int. J. Robot. Res. 30(9), 1100–1123 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of the Balearic Islands, Palma de Mallorca, Spain

    Emilio Garcia-Fidalgo & Alberto Ortiz

Authors
  1. Emilio Garcia-Fidalgo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alberto Ortiz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alberto Ortiz .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Garcia-Fidalgo, E., Ortiz, A. (2018). Loop Closure Detection Using Incremental Bags of Binary Words. In: Methods for Appearance-based Loop Closure Detection. Springer Tracts in Advanced Robotics, vol 122. Springer, Cham. https://doi.org/10.1007/978-3-319-75993-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-75993-7_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75992-0

  • Online ISBN: 978-3-319-75993-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation