Recently, there has been interest in formulating various geometric problems in Computer Vision as L ∞ optimization problems. The advantage of this approach is that under L ∞ norm, such problems typically have a single minimum, and may he efficiently
For reconstruction of a non-negative real valued object based on scanned data in the k-space, it is ...
This paper discusses how to resection camera using image edges extracted from projected polyhedron, ...
We consider the least-squares (L2) minimization problems in multiple view geometry for triangulation...
We investigate the use of the L∞ cost function in geometric vision problems. This cost function meas...
This paper presents a new method for computing optimal L∞ solutions for vision geometry problems, pa...
Minimizing L∞ error norm for some geometric vision problems provides global optimization using the w...
This paper introduces a new algorithmic technique for solving certain problems in geometric computer...
This paper extends the set of problems for which a global solution can be found using modern optimiz...
Efficient solutions to polynomial equation systems is an important topic in modern geometric compute...
We study geometric reconstruction problems in one-dimensional retina vision. In such problems, the s...
This paper proposes a new approach to estimate the camera displacement of stereo vision systems via ...
This paper presents a new framework for solving geometric structure and motion problems based on the...
This paper presents a new framework for solving geometric structure and motion problems based on L∞-...
In this paper, we make a modification to Karl and Hartley‘s formulation of problems in computer visi...
This paper discusses how to resection camera using image edges extracted from projected polyhedron, ...
For reconstruction of a non-negative real valued object based on scanned data in the k-space, it is ...
This paper discusses how to resection camera using image edges extracted from projected polyhedron, ...
We consider the least-squares (L2) minimization problems in multiple view geometry for triangulation...
We investigate the use of the L∞ cost function in geometric vision problems. This cost function meas...
This paper presents a new method for computing optimal L∞ solutions for vision geometry problems, pa...
Minimizing L∞ error norm for some geometric vision problems provides global optimization using the w...
This paper introduces a new algorithmic technique for solving certain problems in geometric computer...
This paper extends the set of problems for which a global solution can be found using modern optimiz...
Efficient solutions to polynomial equation systems is an important topic in modern geometric compute...
We study geometric reconstruction problems in one-dimensional retina vision. In such problems, the s...
This paper proposes a new approach to estimate the camera displacement of stereo vision systems via ...
This paper presents a new framework for solving geometric structure and motion problems based on the...
This paper presents a new framework for solving geometric structure and motion problems based on L∞-...
In this paper, we make a modification to Karl and Hartley‘s formulation of problems in computer visi...
This paper discusses how to resection camera using image edges extracted from projected polyhedron, ...
For reconstruction of a non-negative real valued object based on scanned data in the k-space, it is ...
This paper discusses how to resection camera using image edges extracted from projected polyhedron, ...
We consider the least-squares (L2) minimization problems in multiple view geometry for triangulation...
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