Journal of Mathematical Imaging and Vision

, Volume 60, Issue 4, pp 503–511 | Cite as

Catadioptric Imaging System with a Hybrid Hyperbolic Reflector for Vehicle Around-View Monitoring

Article
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Abstract

A wide field-of-view (FOV) imaging system is essential for a vehicle around-view monitoring system to ensure the safety of driving or parking. This study presents a hybrid hyperbolic reflector for catadioptric wide FOV imaging. It is possible to observe the horizontal side scene as well as the vertical ground scene surrounding a vehicle using the hyperbolic reflector imaging system with a single camera. The image acquisition model is obtained for the hyperbolic reflector imaging system using the geometrical optics in this study. The image acquisition model is the basis of the image reconstruction algorithm to convert the side scene into a panoramic image and the ground scene into a bird’s-eye image to present it in the driver’s display. Both the horizontal panoramic image and the vertical bird’s-eye image surrounding a vehicle are helpful for driving and parking safety.

Keywords

Catadioptric imaging Hybrid hyperbolic reflector Wide FOV Panoramic view Bird’s-eye view Around-view monitoring 
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References

  1. 1.
    Zhang, B., Appia, V., Pekkucuksen, I., Liu, Y.: A surround view camera solution for embedded systems. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops, Ohio, USA, pp. 676–681 (2014)Google Scholar
  2. 2.
    Yebes, J., Alcantarilla, P., Bergasa, L., Gonzalez, A., Almazan, J.: Surrounding view for enhancing safety on vehicles. In: Proceedings of IEEE Intelligent Vehicles Symposium Workshops (2012)Google Scholar
  3. 3.
    Lo, W., Lin, D.: Embedded system implementation for vehicle around view monitoring. In: Proceedings of International Conference on Advanced Concepts for Intelligent Vision Systems(ACIVS 2015), Museo Diocesano, Italy. LNCS 9386, pp. 181–192 (2015)Google Scholar
  4. 4.
    Chen, Y., Tu, Y., Chiu, C., Chen, Y.: Embedded system for vehicle surrounding monitoring. In: Proceedings of IEEE International Conference on Power Electronics and Intelligent Transportation System, pp. 92–95 (2009)Google Scholar
  5. 5.
    Sato, T., Moro, A., Sugahara, A., Tasaki, T., Yamashita, A., Asama, H.: Spatio-temporal bird’s-eye view images using multiple fish-eye cameras. In: Proceedings of IEEE/SICE International Symposium on System Integration, Kobe, Japan, pp. 753–758 (2013)Google Scholar
  6. 6.
    Lin, C., Wang, M.: A vision based top-view transformation model for a vehicle parking assistant. Sensors 12, 4431–4446 (2012)CrossRefGoogle Scholar
  7. 7.
    Jang, G., Kim, S., Kweon, I.: Single camera catadioptric stereo system. In: The 6th Workshop on Omnidirectional Vision, Camera Networks and Non-Classical Cameras (OMNIVIS2005) (2005)Google Scholar
  8. 8.
    Gluckman, J., Nayer, S.: Catadioptric stereo using planner mirrors. Int. J. Comput. Vis. 44(1), 65–79 (2001)CrossRefMATHGoogle Scholar
  9. 9.
    Hicks, R., Bajcsy, R.: Catadioptric sensor that approximate wide-angle perspective projections. In: Proceedings of International Conference on Pattern Recognition’00, pp. 545–551 (2000)Google Scholar
  10. 10.
    Svoboda, T., Pajdlar, T.: Epipolar geometry for central catadioptric cameras. Int. J. Comput. Vis. 49(1), 23–37 (2002)CrossRefMATHGoogle Scholar
  11. 11.
    Micusik, B., Pajdla, T.: Structure from motion with wide circular field of view cameras. IEEE Trans. Pattern Anal. Mach. Intell. 28(7), 1135–1149 (2006)CrossRefGoogle Scholar
  12. 12.
    Nayer, S.: Catadioptric omnidirectional camera. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 482–488 (1997)Google Scholar
  13. 13.
    Baker, S., Nayar, S.: A theory of catadioptric image formation. In: Proceedings of IEEE International Conference on Computer Vision, Bombay, pp. 35–42 (1998)Google Scholar
  14. 14.
    Trivedi, M., Gandhi, T., McCall, J.: Looking-in and looking-out of a vehicle: selected investigations in computer vision based enhanced vehicle safety. IEEE Trans. Intell. Transp. Syst. 8(1), 109–120 (2007)CrossRefGoogle Scholar
  15. 15.
    Ehlgen, T., Pajdla, T., Ammon, D.: Eliminating blind spots for assisted driving. IEEE Trans. Intell. Transp. Syst. 9(4), 657–664 (2008)CrossRefGoogle Scholar
  16. 16.
    Cao, M., Vu, A., Barth, M.: A novel omni-directional vision sensing technique for traffic surveillance. In: Proceedings of IEEE Intelligent Transportation Systems Conference, pp. 648–653 (2007)Google Scholar
  17. 17.
    Kweon, G., Hwang-bo, S., Kim, G., Yang, S., Lee, Y.: Wide-angle catadioptric lens with a rectilinear projection scheme. Appl. Opt. 45(34), 8659–73 (2006)CrossRefGoogle Scholar
  18. 18.
    Kweon, G., Choi, Y., Kim, G., Yang, S.: Extraction of perspectively normal images from video sequences obtained using a catadioptric panoramic lens with the rectilinear projection scheme. In: Technical Proceedings of the 10th World Multi-Conference on Systems, Cybernetics, and Informatics, pp. 67–75 (2006)Google Scholar
  19. 19.
    Vu, A., Barth, M.: Catadioptric omnidirectional vision sensor integration for vehicle-based sensing. In: Proceedings of 12th IEEE Conference on Intelligent Transportation Systems, pp. 120–126 (2009)Google Scholar
  20. 20.
    Yi, S., Ahuja, N.: An omnidirectional stereo vision system using a single camera. In: Proceedings of the 18th International Conference on Pattern Recognition (ICPR’06), pp. 861–865 (2006)Google Scholar
  21. 21.
    Sturzl, W., Boeddeker, N., Dittmar, L., Egelhaaf, M.: Mimicking honeybee eyes with A \(280{^{\circ }}\) field of view catadioptric imaging system. Bioinspiration Biomim. 5, 1–13 (2010)CrossRefGoogle Scholar
  22. 22.
    Cheng, D., Gong, C., Xu, C., Wang, Y.: Design of an ultrawide angle catadioptric lens with an annularly stitched aspherical surface. Opt. Express 24(3), 2664–2677 (2016)CrossRefGoogle Scholar
  23. 23.
    Gluckman, J., Nayar, S.: Catadioptric stereo using planar mirrors. Int. J. Comput. Vis. 44(1), 65–79 (2001)CrossRefMATHGoogle Scholar
  24. 24.
    Sanchez, J., Canton, M.: Space Image Processing. CRC Press, Boca Raton (1998)Google Scholar
  25. 25.
    Schonbein, M., Straus, T., Geiger, A.: Calibrating and centering quasi-central catadioptric cameras. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), pp. 4443–4450 (2014)Google Scholar
  26. 26.
    Perditoto, L., Araujo, H.: Estimation of mirror shape and extrinsic parameters in axial catadioptric systems. Image Vis. Comput. 54, 45–59 (2016)CrossRefGoogle Scholar
  27. 27.
  28. 28.
    Geyer, C., Daniilidis, K.: A unifying theory for central panoramic systems and practical implications. In: Proceedings of European Conference on Computer Vision (ECCV2000), pp. 445–461 (2000)Google Scholar
  29. 29.
    Jain, R., Kasturi, R., Schunck, B.: Machine Vision. McGraw-Hill, New York (1995)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Seoul National University of Science and TechnologySeoulRepublic of Korea

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