Computer Vision and Image Understanding
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Solving the Sum-of-Ratios Problem by an Interior-Point Method
Journal of Global Optimization
Semidefinite Relaxations of Fractional Programs via Novel Convexification Techniques
Journal of Global Optimization
Using concave envelopes to globally solve the nonlinear sum of ratios problem
Journal of Global Optimization
International Journal of Computer Vision - Marr Prize Special Issue
Convex Optimization
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
How Hard is 3-View Triangulation Really?
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Globally Optimal Estimates for Geometric Reconstruction Problems
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Multiple View Geometry and the L_"-norm
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Globally Optimal Estimates for Geometric Reconstruction Problems
International Journal of Computer Vision
Practical Global Optimization for Multiview Geometry
International Journal of Computer Vision
Supervised dimensionality reduction via sequential semidefinite programming
Pattern Recognition
Fast and Stable Polynomial Equation Solving and Its Application to Computer Vision
International Journal of Computer Vision
Triangulation of points, lines and conics
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Optimal algorithms in multiview geometry
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Fast optimal three view triangulation
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Pose estimation from multiple cameras based on Sylvester's equation
Computer Vision and Image Understanding
A branch-and-bound algorithm for globally optimal camera pose and focal length
Image and Vision Computing
Globally Optimal Algorithms for Stratified Autocalibration
International Journal of Computer Vision
Subspace embeddings for the L1-norm with applications
Proceedings of the forty-third annual ACM symposium on Theory of computing
Planar scene modeling from quasiconvex subproblems
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Numerically stable optimization of polynomial solvers for minimal problems
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
A pure L1-norm principal component analysis
Computational Statistics & Data Analysis
Hi-index | 0.00 |
This paper presents a practical method for finding the provably globally optimal solution to numerous problems in projective geometry including multiview triangulation, camera resectioning and homography estimation. Unlike traditional methods which may get trapped in local minima due to the non-convex nature of these problems, this approach provides a theoretical guarantee of global optimality. The formulation relies on recent developments in fractional programming and the theory of convex underestimators and allows a unified framework for minimizing the standard L2-norm of reprojection errors which is optimal under Gaussian noise as well as the more robust L1-norm which is less sensitive to outliers. The efficacy of our algorithm is empirically demonstrated by good performance on experiments for both synthetic and real data. An open source MATLAB toolbox that implements the algorithm is also made available to facilitate further research.