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Automatic free parking space detection by using motion stereo-based 3D reconstruction

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Abstract

This paper proposes a free parking space detection system by using motion stereo-based 3D reconstruction. An image sequence is acquired with a single rearview fisheye camera and the view behind the automobile is three-dimensionally reconstructed by using point correspondences. Metric information is recovered from the camera height ratio and free parking spaces are detected by estimating the positions of adjacent vehicles. Since adjacent vehicles are usually located near the epipole, their structures are seriously degraded. To solve this problem, we select point correspondences by using a de-rotation-based method and mosaic 3D structures by estimating a similarity transformation. Unlike in previous work, our system proposes an efficient way of locating free parking spaces in 3D point clouds. Odometry is not used because its accuracy depends largely on road conditions. In the experiments, the system was tested in 154 different parking situations and its success rate was 90% (139 successes in 154 cases). The detection accuracy was evaluated by using ground truth data that was acquired with a laser scanner.

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References

  1. Armangue X., Salvi J.: Overall view regarding fundamental matrix estimation. Image Vis. Comput. 21(2), 205–220 (2003)

    Article  Google Scholar 

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

    Article  Google Scholar 

  3. Bishop, R.: Intelligent Vehicle Technology and Trends. Artech House Publishers, Norwood (685 Canton Street, Norwood, MA 02062) (2005)

  4. Burger W., Bhanu B.: Estimating 3-D egomotion from perspective image sequences. IEEE Trans. Pattern Anal. Mach. Intell. 12(11), 1040–1058 (1990)

    Article  Google Scholar 

  5. Correia, M.V., Campilho, A.C.: Real-time implementation of an optical flow algorithm. In: Proceedings of the 16th International Conference on Pattern Recognition, vol. 4, pp. 247–250 (2002)

  6. Deacon, C.: New Mercedes CL Class: Parking Assistance Technology. http://www.worldcarfans.com (2006)

  7. Degerman, P., Pohl, J., Sethson, M.: Hough transform for parking space estimation using long range ultrasonic sensors. SAE Paper. Document Number: 2006-01-0810

  8. Díaz J., Ros E., Ortigosa E.M., Mota S.: FPGA-based real-time optical flow system. IEEE Trans. Circuits Syst. Video Technol. 16(2), 274–279 (2006)

    Article  Google Scholar 

  9. Fintzel, K., Bendahan, R., Vestri, C., Bougnoux, S.: 3D parking assistant system. In: Proceedings of IEEE Intelligent Vehicle Symposium, pp. 881–886 (2004)

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

    Article  MathSciNet  Google Scholar 

  11. Fitzgibbon, A., Cross, G., Zisserman, A.: Automatic 3D model construction for turn-table sequences. In: Proceedings of European Workshop on 3D Structure from Multiple Images of Large-Scale Environments, pp. 155–170 (1998)

  12. Gorner, S., Rohling, H.: Parking lot detection with 24 GHz radar sensor. In: The 3rd International Workshop on Intelligent Transportation (2006)

  13. Hartley, R., Zisserman, A.: Multiple view geometry in computer vision, 2nd edn., pp. 204–205, 257–260, 290–292. Cambridge University Press, London (2003)

  14. Huber P.: Robust Statistics. Wiley, New York (1981)

    Book  MATH  Google Scholar 

  15. Jung H.G., Kim D.S., Yoon P.J., Kim J.: 3D vision system for the recognition of free parking site location. Int. J. Automot. Technol. 7(3), 351–357 (2006)

    Google Scholar 

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

  17. Jung, H.G., Cho, Y.H., Yoon, P.J., Kim J.: Integrated side/rear safety system. In: The 11th European Automotive Congress (2007)

  18. 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)

  19. Kaempchen, N., Franke, U., Ott, R.: Stereo vision based estimation of parking lots using 3d vehicle models. In: Proceedings of IEEE Intelligent Vehicle Symposium, pp. 459–464 (2002)

  20. Kageyama, Y.: Look, no hand! New Toyota parks itself. http://www.cnn.com 14 January (2004)

  21. Kelly A.: Linearized error propagation in odometry. Int. J. Robot. Res. 23(2), 179–218 (2004)

    Article  Google Scholar 

  22. Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proceedings of the 7th International Joint Conference on Artificial Intelligence, pp. 674–679 (1981)

  23. Maya-Rueda S., Arias-Estrada M.: FPGA processor for real-time optical flow computation. Lect. Notes Comput. Sci. 2778, 1103–1016 (2003)

    Google Scholar 

  24. McCane B., Novins K., Crannitch D., Galvin B.: On benchmarking optical flow. Comput. Vis. Image Underst. 84(1), 126–143 (2001)

    Article  MATH  Google Scholar 

  25. Moran T.: Self-parking technology hits the market. Automot. News 8(6227), 22–22 (2006)

    Google Scholar 

  26. Mouragnon, E., Dekeyser, F., Sayd, P., Lhuillier, M., Dhome, M.: Real time localization and 3D reconstruction. In: Proceedings of Computer Vision and Pattern Recognition, vol. 1, pp. 17–22 (2006)

  27. Mouragnon, E., Lhuillier, M., Dhome, M., Dekeyser, F., Sayd, P.: Monocular vision based SLAM for mobile robots. In: Proceedings of the 18th International Conference on Pattern Recognition, vol. 3, pp. 20–24 (2006)

  28. Nister D.: Frame decimation for structure and motion. Lect. Notes Comput. Sci. 2018, 17–34 (2001)

    Article  Google Scholar 

  29. Royer E., Lhuillier M., Dhome M., Lavest J.: Monocular vision for mobile robot localization and autonomous navigation. Int. J. Comput. Vis. 74(3), 237–260 (2007)

    Article  Google Scholar 

  30. Satonaka, H., Okuda, M., Hayasaka, S., Endo, T., Tanaka, Y., Yoshida, T.: Development of parking space detection using an ultrasonic sensor. In: The 13th World Congress on Intelligent Transportation Systems and Services (2006)

  31. Schanz, A., Spieker, A., Kuhnert, D.: Autonomous parking in subterranean garages—a look at the position estimation. In: Proceedings of 2003 IEEE Intelligent Vehicle Symposium, pp. 253–258 (2003)

  32. SICK, LD-OEM1000/Laser Measurement Sensors. http://www.sick.com (2007)

  33. Suhr J.K., Jung H.G., Bae K., Kim J.: Outlier rejection for cameras on intelligent vehicles. Pattern Recognit. Lett. 29(6), 828–840 (2008)

    Article  Google Scholar 

  34. Tissainayagam P., Suter D.: Assessing the performance of corner detectors for point feature tracking applications. Image Vis. Comput. 22(8), 663–679 (2004)

    Article  Google Scholar 

  35. Tomasi, C., Shi, J.: Good features to track. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 593–600 (1994)

  36. Torr P., Murray D.: The development and comparison of robust methods for estimating the fundamental matrix. Int. J. Comput. Vis. 24(3), 271–300 (1997)

    Article  Google Scholar 

  37. Torr P., Fitzgibbon A., Zisserman A.: The problem of degeneracy in structure and motion. recovery from uncalibrated image sequences. Int. J. Comput. Vis. 32(1), 27–44 (1999)

    Article  Google Scholar 

  38. Triggs B., McLauchlan P., Hartley R., Fitzgibbon A.: Bundle adjustment—a modern synthesis. Lect. Notes Comput. Sci. 1883, 298–372 (2000)

    Article  Google Scholar 

  39. Trucco E., Verri A.: Introductory techniques for 3-D computer vision. Prentice Hall, Englewood Cliffs (1998)

    Google Scholar 

  40. Umeyama S.: Least-square estimation of transformation parameters between two point patterns. IEEE Trans. Pattern Anal. Mach. Intell. 13(4), 376–380 (1991)

    Article  Google Scholar 

  41. 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 the 8th International IEEE Conference on Intelligent Transportation Systems, pp. 56–60 (2005)

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

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Correspondence to Jaihie Kim.

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Suhr, J.K., Jung, H.G., Bae, K. et al. Automatic free parking space detection by using motion stereo-based 3D reconstruction. Machine Vision and Applications 21, 163–176 (2010). https://doi.org/10.1007/s00138-008-0156-9

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