Advertisement

Robust Place Recognition with Combined Image Descriptors

  • Martin DörflerEmail author
  • Libor Přeučil
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9991)

Abstract

In this paper, a method of place recognition is presented. The method is generally classified under the bag-of-visual-words approach. Information from several global image descriptors is incorporated. The data fusion is performed at the feature level.

The efficacy of the combined descriptor is investigated on the dataset recorded from a real robot. To measure the composition effect, all component descriptors are compared along with their combinations. Information on computational complexity of the method is also detailed, although the algorithms used did not undergo a big amount of optimization. The combined descriptor exhibits greater discriminative power, at the cost of increased computational time.

Keywords

Visual place recognition Robust image features Bag of visual words 

References

  1. 1.
    Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60, 91–110 (2004)CrossRefGoogle Scholar
  2. 2.
    Bay, H., Ess, A., Tuytelaars, T., Van Gool, L., Gool, L.V., Baya, H., Essa, A., Tuytelaarsb, T., Van Goola, L.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110, 346–359 (2008)CrossRefGoogle Scholar
  3. 3.
    Agrawal, M., Konolige, K., Blas, M.R.: CenSurE: center surround extremas for realtime feature detection and matching. In: ECCV 2008, IV, pp. 102–115 (2008)Google Scholar
  4. 4.
    Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximaly stable estreal regions. In: Proceeding of the Britsh Machine Vision Conference, pp. 384–393 (2002)Google Scholar
  5. 5.
    Chung, J., Kim, T., Nam Chae, Y., Yang, H.S.: Unsupervised constellation model learning algorithm based on voting weight control for accurate face localization. Pattern Recogn. 42, 322–333 (2009)CrossRefzbMATHGoogle Scholar
  6. 6.
    Sivic, J., Zisserman, A.: Video Google: a text retrieval approach to object matching in videos. In: 2003 Proceedings of Ninth IEEE International Conference on Computer Vision, vol. 2, pp. 1470–1477 (2003)Google Scholar
  7. 7.
    Cummins, M., Newman, P.: Fab-map: probabilistic localization and mapping in the space of appearance. Int. J. Robot. Res. 27, 647–665 (2008)CrossRefGoogle Scholar
  8. 8.
    Cummins, M., Newman, P.: Appearance-only slam at large scale with FAB-MAP 2.0. Int. J. Robot. Res. 30, 1100–1123 (2011)CrossRefGoogle Scholar
  9. 9.
    Ulrich, I., Nourbakhsh, I.: Appearance-based place recognition for topological localization. In: Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), vol. 2, pp. 1023–1029 (2000)Google Scholar
  10. 10.
    Oliva, A., Torralba, A.: Modeling the shape of the scene: a holistic representation of the spatial envelope. Int. J. Comput. Vis. 42, 145–175 (2001)CrossRefzbMATHGoogle Scholar
  11. 11.
    Liu, Y., Zhang, H.: Visual loop closure detection with a compact image descriptor. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1051–1056 (2012)Google Scholar
  12. 12.
    Snderhauf, N., Protzel, P.: Brief-gist - closing the loop by simple means. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1234–1241 (2011)Google Scholar
  13. 13.
    Murillo, A.C., Guerrero, J.J., Sagues, C.: Surf features for efficient robot localization with omnidirectional images. In: Proceedings of 2007 IEEE International Conference on Robotics and Automation, pp. 3901–3907 (2007)Google Scholar
  14. 14.
    Siagian, C., Itti, L.: Biologically inspired mobile robot vision localization. IEEE Trans. Robot. 25, 861–873 (2009)CrossRefGoogle Scholar
  15. 15.
    Park, D.K., Jeon, Y.S., Won, C.S.: Efficient use of local edge histogram descriptor. In: Proceedings of the 2000 ACM Workshops on Multimedia, MULTIMEDIA 2000, pp. 51–54. ACM, New York (2000)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Cybernetics, Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech Republic
  2. 2.Czech Institute of Informatics, Robotics and CyberneticsCzech Technical University in PraguePragueCzech Republic

Personalised recommendations