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Found 6 papers, 3 papers with code
Calibrated and Partially Calibrated Semi-Generalized Homographies
In this paper, we propose the first minimal solutions for estimating the semi-generalized homography given a perspective and a generalized camera.
A sparse resultant based method for efficient minimal solvers
Our new method can be fully automatized and incorporated into existing tools for automatic generation of efficient polynomial solvers and as such it represents a competitive alternative to popular Gr\"obner basis methods for minimal problems in computer vision.
Automatic Solver Generator for Systems of Laurent Polynomial Equations
The important property of an elimination template is that it applies to all polynomial systems in the family.
Computing stable resultant-based minimal solvers by hiding a variable
The existing state-of-the-art methods for solving such systems are either based on Gr\"obner bases and the action matrix method, which have been extensively studied and optimized in the recent years or recently proposed approach based on a sparse resultant computation using an extra variable.
Partially calibrated semi-generalized pose from hybrid point correspondences
In this paper we study the problem of estimating the semi-generalized pose of a partially calibrated camera, i. e., the pose of a perspective camera with unknown focal length w. r. t.
Sparse resultant based minimal solvers in computer vision and their connection with the action matrix
Most state-of-the-art efficient polynomial solvers are based on the action matrix method that has been automated and highly optimized in recent years.
