Skip to main content
SpringerLink
Log in

3D Visual Odometry for Road Vehicles

  • Unmanned Systems Paper
  • Published:
Journal of Intelligent and Robotic Systems Aims and scope Submit manuscript

Abstract

This paper describes a method for estimating the vehicle global position in a network of roads by means of visual odometry. To do so, the ego-motion of the vehicle relative to the road is computed using a stereo-vision system mounted next to the rear view mirror of the car. Feature points are matched between pairs of frames and linked into 3D trajectories. Vehicle motion is estimated using the non-linear, photogrametric approach based on RANSAC. This iterative technique enables the formulation of a robust method that can ignore large numbers of outliers as encountered in real traffic scenes. The resulting method is defined as visual odometry and can be used in conjunction with other sensors, such as GPS, to produce accurate estimates of the vehicle global position. The obvious application of the method is to provide on-board driver assistance in navigation tasks, or to provide a means for autonomously navigating a vehicle. The method has been tested in real traffic conditions without using prior knowledge about the scene nor the vehicle motion. We provide examples of estimated vehicle trajectories using the proposed method and discuss the key issues for further improvement.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Zhang, Z., Faugeras, O.D.: Estimation of displacements from two 3-D frames obtained from stereo. IEEE Trans. Pattern Anal. Mach. Intell. 14(12), 1141–1156, December (1992)

    Article  Google Scholar 

  2. Nister, D., Narodistsky, O., Beren, J.: Visual odometry. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June (2004)

  3. Hagnelius, A.: Visual odometry. In: Masters Thesis in Computing Science, Umea University, April (2005)

  4. Forsyth, D.A., Ponce, J.: Computer Vision. A Modern Approach (international edn.). Pearson Education International. Prentice Hall (2003)

  5. Agrawal, M., Konolige, K.: Real-time localization in outdoor environments using stereo vision and inexpensive gps. In: 18th International Conference on Pattern Recognition (ICPR06), pp. 1063–1068 (2006)

  6. Simond, N., Parent, M.: Free space in front of an autonomous guided vehicle in inner-city conditions, In: European Computer Aided Systems Theory Conference (Eurocast 2007), pp. 362–363 (2007)

  7. Harris, C., Stephens, M.: A combined corner and edge detector. In: Proceedings of the Fourth Alvey Vision Conference, pp. 147–151 (1988)

  8. Schmid, C., Mohr, R., Bauckhage, C.: Evaluation of interest point detectors. Int. J. Comput. Vis. 37(2), 151–172 (2000)

    Article  MATH  Google Scholar 

  9. Boufama, B.: Reconstruction tridimensionnelle en vision par ordinateur: cas des cameras non etalonnees. Ph.D. thesis, INP de Grenoble, France (1994)

  10. Parra, I., Fernández, D., Sotelo, M.A., Bergasa, L.M., Revenga, P., Nuevo, J., Ocana, M., García, M.A.: Combination of feature extraction methods for SVM pedestrian detection. IEEE Trans. Intell. Transp. Syst. 8(2), 292–307, June (2007)

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  12. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press (2004)

Download references

Author information

Authors and Affiliations

  1. Department of Electronics, Escuela Politécnica Superior, University of Alcalá, Alcalá de Henares, Madrid, Spain

    R. García-García, M. A. Sotelo, I. Parra, D. Fernández & M. Gavilán

  2. Department of Informatics, Industrial Automation Institute, CSIC, Arganda del Rey, Madrid, Spain

    J. E. Naranjo

Authors
  1. R. García-García
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. A. Sotelo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. I. Parra
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. D. Fernández
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. J. E. Naranjo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. Gavilán
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. A. Sotelo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

García-García, R., Sotelo, M.A., Parra, I. et al. 3D Visual Odometry for Road Vehicles. J Intell Robot Syst 51, 113–134 (2008). https://doi.org/10.1007/s10846-007-9182-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-007-9182-5

Keywords

Search

Navigation