Open Access
Issue
E3S Web Conf.
Volume 297, 2021
The 4th International Conference of Computer Science and Renewable Energies (ICCSRE'2021)
Article Number 01055
Number of page(s) 10
DOI https://doi.org/10.1051/e3sconf/202129701055
Published online 22 September 2021
  1. M. Xie, L. Trassoudaine, J. Alizon, J. Gallice, Machine Vision and Applications 7, 165 (1994) [Google Scholar]
  2. I. El Jaafari, M. El Ansari, L. Koutti, A. Ellahyani, S. Charfi, International Journal of Advanced Computer Science & Applications 1, 594 (2016) [Google Scholar]
  3. S. Escalera, O. Pujol, P. Radeva, Machine Vision and Applications 21, 99 (2010) [Google Scholar]
  4. R. Timofte, K. Zimmermann, L. Van Gool, Machine Vision and Applications 25, 633 (2014) [Google Scholar]
  5. A. Ellahyani, M. El Ansari, I. El Jaafari, Applied Soft Computing 46, 805 (2016) [Google Scholar]
  6. A. Ellahyani, M. El Ansari, I. El Jaafari, S. Charfi, International Journal of Advanced Computer Science & Applications 1, 686 (2016) [Google Scholar]
  7. D.M. Gavrila, S. Munder, International Journal of Computer Vision 73, 41 (2006) [Google Scholar]
  8. Y. Geng, 3D Research 7, 27 (2016) [Google Scholar]
  9. S. Barnard, M. Fisher, ACM Comput. Surveys pp. 14:553–572 (1982) [Google Scholar]
  10. A.S. Ogale, Y. Aloimonos, International Journal of Computer Vision 65, 147 (2006) [Google Scholar]
  11. X. Xiang, M. Zhang, G. Li, Y. He, Z. Pan, Machine Vision and Applications 23, 1219 (2012) [Google Scholar]
  12. T.G. Ghazouani, H.R. Zapata, Int. J. Computational Vision and Robotics pp. Vol. 2, No. 3, pp.237–253 (2011) [Google Scholar]
  13. R.M.B.R.B.R. Gupta, G.B. Krishna, Int. J. Computational Vision and Robotics pp. Vol. 2, No. 1, pp.89–98 (2011) [Google Scholar]
  14. S. Zhu, R. Gao, Z. Li, Multimedia Tools and Applications pp. 1–18 (2015) [Google Scholar]
  15. I. El Jaafari, M. El Ansari, L. Koutti, Signal, Image and Video Processing pp. 1–8 (2016) [Google Scholar]
  16. D. Scharstein, R. Szeliski, International Journal of Computer Vision pp. 47(1-3):7–42 (2002) [Google Scholar]
  17. Y. Boykov, O. Veksler, R. Zabih, IEEE Trans. Pattern Analysis and Machine Intelligence pp. 23(11):1222–1239 (2001) [Google Scholar]
  18. V. Kolmogorov, R. Zabih, Int. Conf. on Computer Vision pp. 508–515 (2001) [Google Scholar]
  19. O. Veksler, Ph.D. thesis, Cornell University (1999) [Google Scholar]
  20. L. Hong, G. Chen, Segment-based stereo matching using graph cuts, in IEEE Conf. on Computer Vision and Pattern Recognition (2004), pp. 74–81 [Google Scholar]
  21. M. El Ansari, S. Mousset, A. Bensrhair, A new stereo matching approach for real-time road obstacle detection for situations with deteriorated visibility, in Intelligent Vehicles Symposium, 2008 IEEE (IEEE, 2008), pp. 355–360 [Google Scholar]
  22. M. El Ansari, S. Mousset, A. Bensrhair, Pattern Recognition Letters 31, 1226 (2010) [Google Scholar]
  23. M. El Ansari, S. Mousset, A. Bensrhair, G. Bebis, Temporal consistent fast stereo matching for advanced driver assistance systems (ADAS), in Intelligent Vehicles Symposium (IV), 2010 IEEE (IEEE, 2010), pp. 825–831 [Google Scholar]
  24. A. Mazoul, M. El Ansari, K. Zebbara, G. Bebis, Pattern Analysis and Applications 17, 211 (2014) [Google Scholar]
  25. J. Jiang, J. Cheng, B. Chen, X. Wu, Neurocomputing 142, 335 (2014) [Google Scholar]
  26. I. El Jaafari, M. El Ansari, L. Koutti, A. Mazoul, A. Ellahyani, Neurocomputing 194, 24 (2016) [Google Scholar]
  27. L. Koutti, I.E. Jaafari, M.E. Ansari, Temporal consistent stereo matching approach for road applications, in 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA) (2016), pp. 1–6 [Google Scholar]
  28. J. Davis, D. Nehab, R. Ramamoorthi, S. Rusinkiewicz, IEEE Trans. Pattern Analysis and Machine Intelligence pp. 27(2):1–7 (2005) [Google Scholar]
  29. M. Gong, Enforcing temporal consistency in real-time stereo estimation, in European Conference on Computer Vision (2006), pp. 564–577 [Google Scholar]
  30. H. Tao, H.S. Sawhney, R. Kumar, Dynamic depth recovery from multiple synchronized video streams, in IEEE Int. Conf, on Computer Vision and Pattern Recognition (2001) [Google Scholar]
  31. L. Zhang, B. Curless, S.M. Seitz, Spacetime stereo: shape recovery for dynamic scenes, in IEEE Int. Conf. on Computer Vision and Pattern Recognition (2003), pp. 367–374 [Google Scholar]
  32. S. Vedula, P. Rander, R. Collins, T. Kanade, Pattern Analysis and Machine Intelligence, IEEE Transactions on 27, 475 (2005) [Google Scholar]
  33. S. Vedula, S. Baker, P. Rander, R. Collins, T. Kanade, Three-dimensioal scene flow, in IEEE Int. Conf. on Computer Vision and Pattern Recognition (1991), pp. 722–729 [Google Scholar]
  34. Y. Zhang, C. Kambhamettu, Integrated 3d scene flow and structure recovery from multiview image sequences, in IEEE Int. Conf. on Computer Vision and Pattern Recognition (2000), pp. 674–681 [Google Scholar]
  35. C. Hung, L. Xu, J. Jia, Int. J. Comput. Vision pp. 271–292 (2013) [Google Scholar]
  36. G. Zhang, J. Jia, T. Wong, H. Bao, IEEE Trans. Pattern Analysis and Machine Intelligence pp. 974–988(2009) [Google Scholar]
  37. J. Jiang, J. Cheng, B. Chen, pp. 333–342 (2013) [Google Scholar]
  38. M. Dobias, R. Sara, Real-time global prediction for temporally stable stereo, in IEEE International Conference on Computer Vision Workshops (2011), pp. 704–707 [Google Scholar]
  39. J. Cech, J. Riera, R. Horaud, Scene flow estimation by growing correspondence seeds, in IEEE Conference on Computer Vision and Pattern Recognition (2011), pp. 3129–3136 [Google Scholar]
  40. J. Canny, IEEE Trans Pattern Anal Mach Intell pp. 679–698 (1986) [Google Scholar]
  41. M. Hariti, Y. Ruichek, A. Koukam, A voting stereo matching method for real-time obstacle detection, in Robotics and Automation, 2003. Proceedings. ICRA ’03. IEEE International Conference on (2003), vol. 2, pp. 1700–1704 vol.2, ISSN 1050-4729 [Google Scholar]
  42. K.r. Bae, B. Moon, Multimedia Tools and Applications pp. 1–16 (2016) [Google Scholar]
  43. V. Kolmogorov, P. Monasse, P. Tan, Image Processing On Line 4, 220 (2014) [Google Scholar]
  44. Mars/prescan virtual stereo images, http://stereodatasets.wvandermark.com/ (2006), accessed: 2016 [Google Scholar]

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