PL1P - Point-line Minimal Problems under Partial Visibility in Three Views
暂无分享,去创建一个
Anton Leykin | Tomas Pajdla | Timothy Duff | Kathl'en Kohn | T. Pajdla | Kathlén Kohn | Timothy Duff | A. Leykin
[1] Jan-Michael Frahm,et al. Structure-from-Motion Revisited , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Roland Siegwart,et al. A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation , 2011, CVPR 2011.
[3] Stepán Obdrzálek,et al. Local affine frames for wide-baseline stereo , 2002, Object recognition supported by user interaction for service robots.
[4] Zuzana Kukelova,et al. Making Minimal Solvers for Absolute Pose Estimation Compact and Robust , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[5] Torsten Sattler,et al. Minimal Solvers for Generalized Pose and Scale Estimation from Two Rays and One Point , 2016, ECCV.
[6] Jean Ponce,et al. Trinocular Geometry Revisited , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[7] David Nister,et al. Recent developments on direct relative orientation , 2006 .
[8] Robert C. Bolles,et al. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.
[9] Bernhard P. Wrobel,et al. Multiple View Geometry in Computer Vision , 2001 .
[10] Björn Johansson,et al. Structure and Motion Estimation from Complex Features in Three Views , 2002, ICVGIP.
[11] Matthew Trager. Cameras, Shapes, and Contours: Geometric Models in Computer Vision. (Caméras, formes et contours: modèles géométriques en vision par ordinateur) , 2018 .
[12] Richard I. Hartley,et al. Lines and Points in Three Views and the Trifocal Tensor , 1997, International Journal of Computer Vision.
[13] Roland Siegwart,et al. Finding the Exact Rotation between Two Images Independently of the Translation , 2012, ECCV.
[14] Martin Byröd,et al. A Column-Pivoting Based Strategy for Monomial Ordering in Numerical Gröbner Basis Calculations , 2008, ECCV.
[15] Joe Kileel,et al. Minimal Problems for the Calibrated Trifocal Variety , 2016, SIAM J. Appl. Algebra Geom..
[16] Benjamin B. Kimia,et al. Camera Pose Estimation Using First-Order Curve Differential Geometry , 2012, ECCV.
[17] Levente Hajder,et al. A Minimal Solution for Two-View Focal-Length Estimation Using Two Affine Correspondences , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Andrew Zisserman,et al. Minimal projective reconstruction for combinations of points and lines in three views , 2004, Image Vis. Comput..
[19] Andrew Zisserman,et al. Multiple View Geometry in Computer Vision (2nd ed) , 2003 .
[20] Timothy Duff,et al. Solving polynomial systems via homotopy continuation and monodromy , 2016, ArXiv.
[21] David Nistér,et al. An efficient solution to the five-point relative pose problem , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Torsten Sattler,et al. Efficient & Effective Prioritized Matching for Large-Scale Image-Based Localization , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Timothy Duff,et al. Trifocal Relative Pose from Lines at Points and its Efficient Solution , 2019, ArXiv.
[24] Long Quan,et al. Minimal Projective Reconstruction Including Missing Data , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[25] Timothy Duff,et al. PLMP - Point-Line Minimal Problems in Complete Multi-View Visibility , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[26] G LoweDavid,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004 .
[27] Yubin Kuang,et al. Pose Estimation with Unknown Focal Length Using Points, Directions and Lines , 2013, 2013 IEEE International Conference on Computer Vision.
[28] Peter F. Sturm,et al. Pose estimation using both points and lines for geo-localization , 2011, 2011 IEEE International Conference on Robotics and Automation.
[29] Pedro Miraldo,et al. A Minimal Closed-Form Solution for Multi-Perspective Pose Estimation using Points and Lines , 2018, ECCV.
[30] Pascal Monasse,et al. Robust and Accurate Line- and/or Point-Based Pose Estimation without Manhattan Assumptions , 2016, ECCV.
[31] Jonathan D. Hauenstein,et al. Multiprojective witness sets and a trace test , 2015, Advances in Geometry.
[32] Frank Sottile,et al. Trace Test , 2016, 1608.00540.
[33] Stergios I. Roumeliotis,et al. Optimal estimation of vanishing points in a Manhattan world , 2011, 2011 International Conference on Computer Vision.
[34] S. Shankar Sastry,et al. Rank Conditions on the Multiple-View Matrix , 2004, International Journal of Computer Vision.
[35] Frederik Schaffalitzky,et al. Four Points in Two or Three Calibrated Views: Theory and Practice , 2006, International Journal of Computer Vision.
[36] Benjamin B. Kimia,et al. Multiview Differential Geometry of Curves , 2016, International Journal of Computer Vision.
[37] Ahmed M. Elgammal,et al. Line-based relative pose estimation , 2011, CVPR 2011.
[38] Tomás Pajdla,et al. Neighbourhood Consensus Networks , 2018, NeurIPS.
[39] Richard Szeliski,et al. Modeling the World from Internet Photo Collections , 2008, International Journal of Computer Vision.
[40] Vincent Lepetit,et al. An Efficient Minimal Solution for Multi-camera Motion , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[41] Bernd Sturmfels,et al. Rigid multiview varieties , 2015, Int. J. Algebra Comput..
[42] Zuzana Kukelova,et al. Automatic Generator of Minimal Problem Solvers , 2008, ECCV.
[43] Julie Delon,et al. Accurate Junction Detection and Characterization in Natural Images , 2013, International Journal of Computer Vision.
[44] James R. Bergen,et al. Visual odometry , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[45] Zuzana Kukelova,et al. Beyond Grobner Bases: Basis Selection for Minimal Solvers , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[46] Viktor Larsson,et al. Polynomial Solvers for Saturated Ideals , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[47] Torsten Sattler,et al. InLoc: Indoor Visual Localization with Dense Matching and View Synthesis , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[48] Michel Dhome,et al. Determination of the Attitude of 3D Objects from a Single Perspective View , 1989, IEEE Trans. Pattern Anal. Mach. Intell..
[49] Helder Araújo,et al. Direct Solution to the Minimal Generalized Pose , 2015, IEEE Transactions on Cybernetics.
[50] Peter F. Sturm,et al. Minimal solutions for generic imaging models , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[51] Steven M. Seitz,et al. Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..
[52] Levente Hajder,et al. Efficient Recovery of Essential Matrix From Two Affine Correspondences , 2018, IEEE Transactions on Image Processing.
[53] Daniel Barath,et al. Five-Point Fundamental Matrix Estimation for Uncalibrated Cameras , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[54] Hongdong Li,et al. An Efficient Hidden Variable Approach to Minimal-Case Camera Motion Estimation , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[55] Yubin Kuang,et al. Stratified sensor network self-calibration from TDOA measurements , 2013, 21st European Signal Processing Conference (EUSIPCO 2013).
[56] Rekha R. Thomas,et al. On the Existence of Epipolar Matrices , 2015, International Journal of Computer Vision.
[57] Viktor Larsson,et al. Efficient Solvers for Minimal Problems by Syzygy-Based Reduction , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[58] Rekha R. Thomas,et al. A Hilbert Scheme in Computer Vision , 2011, Canadian Journal of Mathematics.
[59] Luke Oeding,et al. The ideal of the trifocal variety , 2012, Math. Comput..
[60] Homer H. Chen. Pose Determination from Line-to-Plane Correspondences: Existence Condition and Closed-Form Solutions , 1991, IEEE Trans. Pattern Anal. Mach. Intell..
[61] Marc Pollefeys,et al. A minimal solution to the rolling shutter pose estimation problem , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[62] Jan-Michael Frahm,et al. USAC: A Universal Framework for Random Sample Consensus , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[63] Zuzana Kukelova,et al. A Clever Elimination Strategy for Efficient Minimal Solvers , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[64] M. Oskarsson,et al. Classifying and solving minimal structure and motion problems with missing data , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[65] Brett Browning,et al. Evaluating Pose Estimation Methods for Stereo Visual Odometry on Robots , 2010 .