Identification and Recovery of Trajectories of Dynamic Objects from Stereo Images | Programming and Computer Software
Skip to main content
Springer Nature Link
Log in

Identification and Recovery of Trajectories of Dynamic Objects from Stereo Images

  • Published:
Programming and Computer Software Aims and scope Submit manuscript

Abstract

A modified approach to recovering the trajectories of dynamic objects in a scene from stereo images is proposed. This approach is based on the use of an extended point representation of objects, visual odometry, and a novel set of algorithms. Object identification algorithms and the block diagram of the step-by-step data processing are described. Results of numerical experiments for synthetic scenes are presented.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

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

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

REFERENCES

  1. Bobkov V.A., Kudryashov, A.P., and Mel’man, S.V. On the recovery of motion of dynamic objects from stereo images, Program. Comput. Software, 2018, vol. 44, no. 4, pp. 148–158.

    Article  Google Scholar 

  2. Hasler, N., Rosenhahn, B., Thormahlen, T.,Wand, M., Gall, J., and Seidel, H.P., Markerless motion capture with unsynchronized moving cameras, Conf. on Computer Vision and Pattern Recognition, 2009, pp. 224–231.

    Book  Google Scholar 

  3. Ballan, L., Brostow, G.J., Puwein, J., aand Pollefeys, M., Unstructured video-based rendering: Interactive exploration of casually captured videos, ACM Trans. Graphics, Proc. of SIGGRAPH, 2010, pp. 134–146.

  4. Taneja, A., Ballan, L., and Pollefeys, M., Modeling dynamic scenes recorded with freely moving cameras, Conf. on Computer Vision, 2011, pp. 613–626.

    Book  Google Scholar 

  5. Wedel, A., Brox, T., Vaudrey, T., Rabe, C., Franke, U., and Cremers, D., Stereoscopic scene flow computation for 3D motion understanding, Intl. J. Comput. Vision, 2011, vol. 35, no. pp. 29–51.

  6. Alcantarilla, P., Yebes, J., Almazn, J., and Bergasa, L., On combining visual SLAM and dense scene flow to increase the robustness of localization and mapping in dynamic environments, Int. Conf. on Robotics and Automation, 2012, pp. 1290–1297.

  7. Keller, M., Lefloch, D., Lambers, M., Izadi, S., Weyrich, T., and Kolb, A., Real-time 3D reconstruction in dynamic scenes using point-based fusion, in Proc. of the Joint 3DIM/3DPVT Conference (3DV), 2013, pp. 1–8.

  8. Mustafa, A., Kim, H., Guillemaut, J.-Y., and Hilton, A., General dynamic scene reconstruction from multiple view video, in Proc. of the IEEE Int.Conf. on Computer Vision, 2015, pp. 900–908.

    Google Scholar 

  9. Mustafa, A., Kim, H., Guillemaut, J-Y., and Hilton, A., Temporally coherent 4D reconstruction of complex dynamic scenes, IEEE Conf. on Computer Vision and Pattern recognition, 2016, pp. 223–245.

  10. Lefloch, D., Kluge, M., Sarbolandi, H., Weyrich, T., and Kolb, A., Comprehensive use of curvature for robust and accurate online surface reconstruction, IEEE Trans. Pattern Anal. Mach. Intell., 2017, Vol. 39, no. 12, pp. 2349–2365.

    Article  Google Scholar 

  11. Kamaev, A.N., Sukhenko, V.A., and Karmanov, D.A., Constructing and visualizing three-dimensional sea bottom models to test AUV machine vision systems, Program.Comput. Software, 2017, vol. 43, no. 3, pp. 184–195.

    Article  MathSciNet  Google Scholar 

  12. Zolotov, V.A., Petrishchev, K.S., and Semenov, V.A., Methods of spatial indexing of dynamic scenes based on regular octrees, Program.Comput. Software, 2016, vol. 42, no. 6, pp. 375–381.

    Article  MathSciNet  Google Scholar 

  13. Bobkov, V.A. and Ronshin, Y.I., GPU implementation of depth map algorithm, The First Russia and Pacific Conference on Computer Technology and Applications, Vladivostok, 2010, pp. 382-387.

  14. Bobkov, V.A., Ron’shin, Yu.I., Kudryashov, A.P., and Mashentsev, V.Yu., 3D SLAM from Stereoimages, Program.Comput. Software, 2014, vol. 40, no. 4, pp. 159–165.

    Article  Google Scholar 

  15. Bobkov, V.A., Melman, S.V., and Kudryashov, A.P., Fast computation of local displacement by stereo pairs, Pattern Recognit. Image Anal., 2017, no. 3, pp. 458–465.

  16. Bobkov, V.A., Kudryashov, A.P., Mel’man, S.V., and Shcherbatyuk, A.F., Autonomous underwater navigation with 3D environment modeling using stereo images, Gyroscopy Navigation, 2018, vol. 9, no. 1, pp. 67–75.

    Article  Google Scholar 

  17. Bay, H., Ess, A., Tuytelaars, T., and Van Gool, L., Speeded-Up Robust Features (SURF), Comput. Vision Image Understanding, 2008, vol. 110, pp. 346–359.

    Article  Google Scholar 

  18. Lucas, B.D. and Kanade, T., An iterative image registration technique with an application to stereo vision, Int. Joint Conf. on Artificial Intelligence, 1981, pp. 674–679.

Download references

Funding

This work was supported by the Russian Foundation for Basic Research, project no. 18-07-00165.

Author information

Authors and Affiliations

  1. Institute of Automation and Control Processes, Far East Branch of the Russian Academy of Sciences, 690041, Vladivostok, Russia

    V. A. Bobkov & A. P. Kudryashov

Authors
  1. V. A. Bobkov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. P. Kudryashov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to V. A. Bobkov or A. P. Kudryashov.

Additional information

Translated by A. Klimontovich

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bobkov, V.A., Kudryashov, A.P. Identification and Recovery of Trajectories of Dynamic Objects from Stereo Images. Program Comput Soft 46, 1–11 (2020). https://doi.org/10.1134/S0361768820010028

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0361768820010028

Search

Navigation