Robust and Accurate Cylinder Triangulation
This work addresses a specific problem in computer vision for 3D reconstruction from images, but it is incremental as it builds on existing triangulation methods with improvements in robustness and accuracy.
The paper tackles the problem of triangulating infinite cylinders from image line silhouettes by addressing the ill-posed nature of linear quadric estimation, proposing a method that constrains conic sections to circles and uses algebraic constraints on the dual conic. It results in a fast minimal solver for robust estimation and a constrained least squares solver, showing accurate performance on synthetic and real data compared to previous methods.
In this paper we present methods for triangulation of infinite cylinders from image line silhouettes. We show numerically that linear estimation of a general quadric surface is inherently a badly posed problem. Instead we propose to constrain the conic section to a circle, and give algebraic constraints on the dual conic, that models this manifold. Using these constraints we derive a fast minimal solver based on three image silhouette lines, that can be used to bootstrap robust estimation schemes such as RANSAC. We also present a constrained least squares solver that can incorporate all available image lines for accurate estimation. The algorithms are tested on both synthetic and real data, where they are shown to give accurate results, compared to previous methods.