Skip to main content
SpringerLink
Log in

Real-time optical markerless tracking for augmented reality applications

  • Special Issue
  • Published:
Journal of Real-Time Image Processing Aims and scope Submit manuscript

Abstract

Augmented reality (AR) technology consists in adding computer-generated information (2D/3D) to a real video sequence in such a manner that the real and virtual objects appear coexisting in the same world. To get a realistic illusion, the real and virtual objects must be properly aligned with respect to each other, which requires a robust real-time tracking strategy—one of the bottlenecks of AR applications. In this paper, we describe the limitations and advantages of different optical tracking technologies, and we present our customized implementation of both recursive tracking and tracking by detection approaches. The second approach requires the implementation of a classifier and we propose the use of a Random Forest classifier. We evaluated both approaches in the context of an AR application for design review. Some conclusions regarding the performance of each approach are given.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Barandiaran, I., Cottez, C., Paloc, C., Graña, M.: Random forest classifier for real-time optical markerless tracking. Proc. VISAPP 2, 559–564 (2008). ISBN:978-989-8111-21-0

  2. Barandiaran, I., Cottez, C., Paloc, C., Graña, M.: Comparative evaluation of Random Forest and Fern classifiers for real-time feature matching. In: Proceedings of WSCG, pp. 59–166 (2008). ISBN:978-80-86943-15-2

  3. Boffy, A., Tsin, Y., Genc, Y.: Real-time feature matching using adaptative and spatially distributed classification trees. Proc. BMVC 2, 529–539 (2006)

    Google Scholar 

  4. Breiman, L.: Random forests. Mach. Learn. J. 45, 5–32 (2001)

    Article  MATH  Google Scholar 

  5. Chandaria, J., Graham, T., Stricker, D.: The MATRIS project: real-time markerless camera tracking for Augmented Reality and broadcast applications. J. Real Time Image Process. 2, 69–79 (2007). doi:10.1007/s11554-007-0043-z

    Article  Google Scholar 

  6. Davison, A.J., Mayol, W., Murray, D.W.: Real-time localisation and mapping with wearable active vision. In: Proceedings of ISMAR (2003)

  7. 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, 381–395 (1981)

    Google Scholar 

  8. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, London (2004). ISBN:0521-54051-8

  9. Harris, C. Stephens, M.J.: A combined corner and edge detector. In: Alvey Vision Conference, pp. 147–152 (1988)

  10. Lepetit, V., Pilet, J., Fua, P.: Point matching as a classification problem for fast and robust object pose estimation. In: Proceedings of CVPR, vol. 2, pp. 244–250 (2004). ISSN: 1063-6919

  11. Lepetit, V., Fua, P.: Monocular model-based 3D object tracking of rigid objects: a survey. Found. Trends Comput. Graph. Vis. 1, 1–89 (2005)

    Google Scholar 

  12. Lepetit, V., Fua, P.: Keypoint recognition using randomized trees. IEEE Trans. Pattern Anal. Mach. Intell. 28(9), 1465–1479 (2006). ISSN: 0162-8828

    Google Scholar 

  13. Lowe, D.: Distinctive image features from scale invariants keypoints. Int. J. Comput. Vis. 20(2), 91–110 (2004)

    Article  Google Scholar 

  14. Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Gool, L.V.: A comparison of affine region detectors. Int. J. Comput. Vis. 65(1–2), 43–72 (2005). ISSN: 0920-5691

    Google Scholar 

  15. Özuysal, M., Fua, P., Lepetit, V.: Feature harvesting for tracking-by-detection. In: Proceedings of European Conference on Computer Vision, pp. 592–605 (2006). ISBN:3-540-33836-5

  16. Reitmayr, G., Schmalstieg, D.: OpenTracker: a flexible software design for three-dimensional interaction. Virtual Real. J. 9, 79–92 (2005). doi:10.1007/s10055-005-0006-2

    Article  Google Scholar 

  17. Rosten, E., Drummond, T.: Machine learning for high-speed corner detection. In: Proceedings of European Conference on Computer Vision, pp. 430–443 (2006). ISBN:3540338322

  18. Vacchetti, L., Lepetit, V., Fua, P.: Combining edge and texture information for real-time accurate 3D camera tracking. In: Proceedings of IEEE and AM International Symposium on Mixed and Augmented Reality, vol. 4, pp. 48–57 (2004). ISBN:0-7695-2191-6

  19. Williams, B., Klein, G., Reid, I.: Real-time SLAM relocalisation. In: Proceedings of IEEE International Conference on Computer Vision, pp. 1–8 (2007)

  20. Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000). doi:10.1109/34.888718

    Article  Google Scholar 

  21. Lepetit, V.: On computer vision for augmented reality. In: Proceedings of the International Symposium on Ubiquitous Virtual Reality, pp. 13–16 (2008)

Download references

Acknowledgments

This work has been partially funded under the sixth Framework Programme of the European Union (EU) within the project “IMPROVE”: IST FP6- 004785.

Author information

Authors and Affiliations

  1. VICOMTech, Paseo Mikeletegi, 57, 20009, San Sebastián, Spain

    Iñigo Barandiaran, Céline Paloc & Manuel Graña

Authors
  1. Iñigo Barandiaran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Céline Paloc
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Manuel Graña
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Iñigo Barandiaran.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Barandiaran, I., Paloc, C. & Graña, M. Real-time optical markerless tracking for augmented reality applications. J Real-Time Image Proc 5, 129–138 (2010). https://doi.org/10.1007/s11554-009-0140-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11554-009-0140-2

Keywords

Search

Navigation