IMAGE STITCHING METHOD BASED ON PROJECTIVE INTERPOLATION

Le Zhang, Dong Ren, Zhiyong Huang, Shuanghui Lei, and Chong Zhang

References

  1. [1] R. Szeliski, Image alignment and stitching: A tutorial, Foundations & Trends r in Computer Graphics & Vision, 2(1), 2006, 1–104.
  2. [2] C.H. Chang, Y. Sato, and Y.Y. Chuang, Shape-preserving half-projective warps for image stitching, 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014, 3254–3261.
  3. [3] J. Zaragoza, T.J. Chin, M.S. Brown, and D. Suter, As-projective-as-possible image stitching with moving DLT, IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(7), 2014, 1285–1298.
  4. [4] J.W. Lee and I.S. Kweon, Image point feature matching by triangulation, Intelligent Automation & Soft Computing, 3(2), 1997, 135–149.
  5. [5] D. Ren, Y.M. Liu, X.D. Yang, J.H. Wang, and H.Y. Yu, An improved PCA fusion method based on generalized intensity– hue–saturation fusion technique, Intelligent Automation and Soft Computing, 18(18), 2012, 1165–1175.
  6. [6] R. Carroll, M. Agrawal, and A. Agarwala, Optimizing content-preserving projections for wide-angle images, Acm Transactions on Graphics, 28(3), 2009, 341–352.
  7. [7] J. Gao, S.J. Kim, and M.S. Brown, Constructing image panoramas using dual-homography warping, IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, 42, 2011, 49–56.
  8. [8] W.Y. Lin, S. Liu, Y. Matsushita, T.T. Ng, and L.F. Cheong, Smoothly varying affine stitching, IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, 32, 2011, 345–352.
  9. [9] F. Zhang and F. Liu, Parallax-Tolerant Image Stitching, IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, Washington, DC, USA, 2014, 3262–3269.
  10. [10] V. Kwatra, A. Schödl, I. Essa, G. Turk, and A. Bobick, Graphcut textures: Image and video synthesis using graph cuts, ACM Transactions on Graphics, 22(3), 2003, 277–286.
  11. [11] Jr. Ford, R. Lester, and D.R. Fulkerson, Flows in networks, Mathematics of Computation, 18(4), 2009, 157–172.
  12. [12] Y. Boykov and V. Kolmogorov, An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision, IEEE Transactions on Pattern Analysis & Machine Intelligence, 26(9), 2004, 1124–1137.
  13. [13] K. Shoemake and T. Duff, Matrix animation and polar decomposition, Proceedings of the Conference on Graphics Interface, 92, 1992, 258–264.
  14. [14] T.Y. Wong, P. Kovesi, and A. Datta, Projective transformations for image transition animations, Image Analysis and Processing, 2007. ICIAP 2007. 14th International Conference on IEEE, 2007, 493–500.
  15. [15] H.J. Asl, G. Oriolo, and H. Bolandi, An adaptive scheme for image-based visual servoing of an underactuated UAV, International Journal of Robotics and Automation, 29(1), 2014, 92–104.

Important Links:

Go Back