Skip to main content
Log in

Parking assistance using dense motion-stereo

Real-time parking slot detection, collision warning and augmented parking

  • Special Issue Paper
  • Published:
Machine Vision and Applications Aims and scope Submit manuscript


The ability of generating and interpreting a three-dimensional representation of the environment in real-time is one of the key technologies for autonomous vehicles. While active sensors like ultrasounds have been commercially used, their cost and precision is not favorable. On the other hand, integrating passive sensors, like video cameras, in modern vehicles is quite appealing especially because of their low cost. However, image processing requires reliable real-time algorithms to retrieve depth from visual information. In addition, the limited processing power in automobiles and other mobile platforms makes this problem even more challenging. In this paper we introduce a parking assistance system which relies on dense motion-stereo to compute depth maps of the observed environment in real-time. The flexibility and robustness of our method is showcased with different applications: automatic parking slot detection, a collision warning for the pivoting ranges of the doors and an image-based rendering technique to visualize the environment around the host vehicle. We evaluate the accuracy and reliability of our system and provide quantitative and qualitative results. A comparison to ultrasound and feature-based motion-stereo solutions shows that our approach is more reliable.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others


  1. Barron J.L., Fleet D.J., Beauchemin S.S.: Performance of optical flow techniques. Int. J. Comput. Vis. 12(1), 43–77 (1994)

    Google Scholar 

  2. Brunton, A., Shu, C., Roth, G.: Belief propagation on the gpu for stereo vision. In: Canadian Conference on Computer and Robot Vision, pp. 76–81 (2006)

  3. Devernay F., Faugeras O.D.: Straight lines have to be straight. Mach. Vis. Appl. 13(1), 14–24 (2001)

    Article  Google Scholar 

  4. Faugeras, O., Hotz, B., Mathieu, H., Viéville, T., Zhang, Z., Fua, P., Théron, E., Moll, L., Berry, G., Vuillemin, J., Bertin, P., Proy, C.: Real time correlation-based stereo: algorithm, implementations and applications. Tech. Rep. RR-2013, INRIA (1993)

  5. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient belief propagation for early vision. In: CVPR (2004)

  6. Fintzel, K., Bendahan, R., Bougnoux, S.: 3d parking assistant system. In: Proceedings of IEEE Intelligent Vehicles Symposium, pp. 881–886 (2004)

  7. Hirschmüller, H.: Accurate and efficient stereo processing by semi-global matching and mutual information. In: CVPR, pp. 807–814 (2005)

  8. Hirschmüller H., Innocent P.R., Garibaldi J.: Real-time correlation-based stereo vision with reduced border errors. Int. J. Comput. Vis. 47(1–3), 229–246 (2002)

    MATH  Google Scholar 

  9. Jung, H.G., Kim, D.S., Yoon, P.J.: Parking slot markings recognition for automatic parking assist system. In: Proceedings of IEEE Intelligent Vehicles Symposium, pp. 106–113 (2006)

  10. Jung, H.G., Kim, D.S., Yoon, P.J., Kim, J.: Light stripe projection based parking space detection for intelligent parking assist system. In: Proceedings of IEEE Intelligent Vehicle Symposium (2007)

  11. Kämpchen, N., Franke, U., Ott, R.: Stereo vision based pose estimation of parking lots using 3d vehicle models. In: Proceedings of IEEE Intelligent Vehicle Symposium (2002)

  12. Klappstein, J., Stein, F., Franke, U.: Monocular motion detection using spatial constraints in a unified manner. In: Proceedings of IEEE Intelligent Vehicle Symposium, pp. 261–267 (2006)

  13. Kolmogorov, V., Zabih, R.: Computing visual correspondence with occlusions using graph cuts. In: ICCV, pp. 508–515 (2001)

  14. Lu Y., Zhang J.Z., Wu Q.M.J., Li Z.N.: A survey of motion-parallax-based 3-d reconstruction algorithms. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 34(4), 532–548 (2004)

    Article  Google Scholar 

  15. Merrell, P., Akbarzadeh, A., Wang, L., Frahm, J.M., Yang, R., Nistér, D.: Real-time visibility-based fusion of depth maps. In: ICCV, pp. 1–8 (2007)

  16. Mühlmann K., Maier D., Hesser J., Männer R.: Calculating dense disparity maps from color stereo images, an efficient implementation. Int. J. Comput. Vis. 47(1–3), 79–88 (2002)

    MATH  Google Scholar 

  17. Nistér, D.: Frame decimation for structure and motion. In: 3D Structure from Images-SMILE 2000, LNCS, pp. 17–34. Springer, Berlin (2001)

  18. Park, W.J., Kim, B.S., Seo, D.E., Kim, D.S., Lee, K.H.: Parking space detection using ultrasonic sensor in parking assistance system. In: Proceedings of IEEE Intelligent Vehicle Symposium, pp. 1039–1044 (2008)

  19. Pohl J., Sethsson M., Degerman P., Larsson J.: A semi-automated parallel parking system for passenger cars. Proc. Inst. Mech. Eng. Part D J. Automob. Eng. 220, 53–65 (2006)

    Article  Google Scholar 

  20. Pruckner, A., Gensler, F., Meitinger, K.H., Gräf, H., Spannheimer, H., Gresser, K.: Der parkassistent—ein weiteres innovatives fahrerassistenzsystem zum thema connecteddrive aus der bmw-fahrzeugforschung. In: Braunschweiger Symposium (2003)

  21. Rosenberg, I.D., Davidson, P.L., Muller, C.M.R., Han, J.Y.: Real-time stereo vision using semi-global matching on programmable graphics hardware. In: SIGGRAPH 2006 Sketches (2006)

  22. Schanz, A.: Fahrerassistenz zum automatischen Parken. No. 607 in 12. VDI Verlag (2005)

  23. Scharstein D., Szeliski R., Zabih R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Int. J. Comput. Vis. 47, 7–42 (2002)

    Article  MATH  Google Scholar 

  24. Scheunert, U., Fardi, B., Mattern, N., Wanielik, G., Keppeler, N.: Free space determination for parking slots using a 3d pmd sensor. In: Proceedings of IEEE Intelligent Vehicle Symposium, pp. 154–159 (2007)

  25. Song, K.T., Chen, H.Y.: Lateral driving assistance using optical flow and scene analysis. In: Proceedings of IEEE Intelligent Vehicle Symposium, pp. 624–629 (2007)

  26. Stahl, W., Hoetzel, J.: Parktronic-system (pts), aktueller stand und ausblick. Tech. Rep. 1287, VDI-Berichte (1996)

  27. Suhr, J.K., Bae, K., Kim, J., Jung, H.G.: Free parking space detection using optical flow-based euclidean 3d reconstruction. In: MVA, pp. 563–566 (2007)

  28. Suhr J.K., Jung H.G., Bae K., Kim J.: Automatic free parking space detection by using motion stereo-based 3d reconstruction. Mach. Vis. Appl. 21(2), 163–176 (2010)

    Article  Google Scholar 

  29. Torr P.H.S., Murray D.W.: The development and comparison of robust methods for estimating the fundamental matrix. Int. J. Comput. Vis. 24, 271–300 (1997)

    Article  Google Scholar 

  30. Unger, C., Benhimane, S., Wahl, E., Navab, N.: Efficient disparity computation without maximum disparity for real-time stereo vision. In: BMVC (2009)

  31. Unger, C., Wahl, E., Ilic, S.: Efficient stereo matching for moving cameras and decalibrated rigs. Intell. Veh. 417–422 (2011)

  32. Unger, C., Wahl, E., Sturm, P., Ilic, S.: Probabilistic disparity fusion for real-time motion-stereo. Tech. rep., Technische Universität München (2010).

  33. Vestri, C., Bougnoux, S., Bendahan, R., Fintzel, K., Wybo, S., Abad, F., Kakinami, T.: Evaluation of a vision-based parking assistance system. In: Proceedings of IEEE Intelligent Vehicle Symposium, pp. 131–135 (2005)

  34. Wahl, E., Oszwald, F., Ruß, A., Zeller, A., Rossberg, D.: Evaluation of automotive vision systems: Innovations in the development of video-based adas. In: FISITA World Automotive Congress (2008)

  35. Wahl, E., Strobel, T., Ruß, A., Rossberg, D., Therburg, R.D.: Realisierung eines parkassistenten basierend auf motion-stereo. In: 16. Aachener Kolloquium (2007)

  36. Wahl, E., Therburg, R.D.: Developing a motion-stereo parking assistant at bmw. MATLAB Digest (2008)

  37. Wahl, E., Zeitler, W.: Video-based driver assistance systems put to test: Comparison—evaluation—series production. In: 13th International Conference: Electronic Systems for Vehicles (2007)

  38. Wang, L., Liao, M., Gong, M., Yang, R., Nister, D.: High-quality real-time stereo using adaptive cost aggregation and dynamic programming. In: Proc. Int. Symp. 3D Data Proc., Vis., and Transm. (3DPVT), pp. 798–805 (2006)

  39. Xu, J., Chen, G., Xie, M.: Vision-guided automatic parking for smart car. In: Proceedings of IEEE Intelligent Vehicles Symposium, pp. 725–730 (2000)

  40. Zach, C.: Fast and high quality fusion of depth maps. In: 3DPVT (2008)

  41. Zhang, G., Jia, J., Wong, T.T., Bao, H.: Recovering consistent video depth maps via bundle optimization. In: CVPR, pp. 1–8 (2008)

  42. Zhang Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22, 1330–1334 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Christian Unger.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Unger, C., Wahl, E. & Ilic, S. Parking assistance using dense motion-stereo. Machine Vision and Applications 25, 561–581 (2014).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: