Relative Pose Estimation Method in Multi-view 3D Reconstruction with Unknown Distortion

XUE Jun-shi; SHU Qi-quan; GUO Ning-bo

doi:10.3788/gzxb20184706.0612002

[1] LONGUET H C. A computer algorithm for reconstructing a scene from two projections［J］. Nature, 1981, 293(5828): 133-135.

[2] LUONG Q T, FAUGERAS O D. The fundamental matrix: Theory, algorithms, and stability analysis［J］. International Journal of Computer Vision, 1996, 17(1): 43-75.

[3] ARMANGUE X, SALVI J. Overall view regarding fundamental matrix estimation ［J］. Image & Vision Computing, 2003, 21(2): 205-220.

[4] STEWENIUS H, NISTER D, KAHL F, et al. A minimal solution for relative pose with unknown focal length［C］. Computer Vision and Pattern Recognition, IEEE, 2005(2): 789-794.

[5] STEWENIUS H, ENGELS C, NISTER D. Recent developments on direct relative orientation［J］. Isprs Journal of Photogrammetry & Remote Sensing, 2006, 60(4): 284-294.

[6] ARMAMGUE X, SALVI J. Overall view regarding fundamental matrix estimation ［J］. Image & Vision Computing, 2003, 21(2): 205-220.

[7] FITZGIBBON A W. Simultaneous linear estimation of multiple view geometry and lens distortion［C］. Computer Vision and Pattern Recognition, Proceedings of the 2001 IEEE Computer Society Conference on IEEE, 2001(1): 125-132.

[8] BARRETO J P, DANIILIDIS K. Fundamental matrix for cameras with radial distortion［C］. Tenth IEEE International Conference on Computer Vision, IEEE Computer Society, 2005: 625-632.

[9] KUKELOVA Z, BUJNAK M, PAJDLA T. Automatic generator of minimal problem solvers［C］. European Conference on Computer Vision, 2008: 302-315.

[10] BYROD M, KUKELOVA Z, JOSEPHSON K, et al. Fast and robust numerical solutions to minimal problems for cameras with radial distortion［C］. Computer Vision and Pattern Recognition, IEEE , 2010: 1-8.

[11] KUANG Y, SOLEM J E, KAHL F, et al. Minimal solvers for relative pose with a single unknown radial distortion［C］. Computer Vision and Pattern Recognition, 2014: 33-40.

[12] JIANG F, KUANG Y, SOLEM E, et al. A minimal solution to relative pose with unknown focal length and radial distortion［M］. Computer Vision, ACCV 2014. Springer International Publishing, 2014: 443-456.

[13] KUKELOVA Z, HELLER J, BUNJNAK M, et al. Efficient solution to the epipolar geometry for radially distorted cameras［C］. IEEE International Conference on Computer Vision, 2015: 2309-2317.

[14] KUKELOVA Z, HELLER J, BUJNAK M, et al. Radial distortion homography［C］. Computer Vision and Pattern Recognition, IEEE, 2015: 639-647.

[15] LI H, HARTLER R. A non-iterative method for correcting lens distortion from nine point correspondences［J］. OMNIVIS, 2005: 2-7.

[16] HENRIQUE B J, ANGST R, KOSER K, et al. Radial distortion self-calibration［C］. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2013: 1368-1375.

[17] BRITO J H, ANGST R, KOSER K, et al. Unknown radial distortion centers in multiple view geometry problems［C］. Asian Conference on Computer Vision, Springer, 2012: 136-149.

[18] YUAN Xiao-yu, CHEN Shi-yu, ZHONG Can. Oblique aerial image relative orientation based on fundamental matrix［J］. Geomatics & Information Science of Wuhan University, 2016, 41(8): 995-1000.

[19] ZHOU Fan, SHAO Shi-xiong, WU Jian-hua. Method for fundamental matrix estimation combined with line features［J］. Acta Optica Sinica, 2013, 33(10): 188-195.