Accurate and robust estimation of the Fundamental matrix is very important for many computer vision applications, such as 3D reconstruction from 2D images. In this paper, a complete analysis and comparison of three important algorithms for estimating the Fundamental matrix when three views are given. The six-point algorithm originally used for three-view geometry is implemented for the automati...

We classify and review existing algorithms for computing the fundamental matrix from point correspondences and propose new effective schemes: 7-parameter Levenberg-Marquardt (LM) search, EFNS, and EFNS-based bundle adjustment. Doing experimental comparison, we show that EFNS and the 7-parameter LM search exhibit the best performance and that additional bundle adjustment does not increase the ac...

in this paper, an iterative method is proposed for solving matrix equation $sum_{j=1}^s a_jx_jb_j = e$. this method is based on the global least squares (gl-lsqr) method for solving the linear system of equations with the multiple right hand sides. for applying the gl-lsqr algorithm to solve the above matrix equation, a new linear operator, its adjoint and a new inner product are dened. it is ...

In this paper, we propose a novel method for synthesizing super-resolved images from image sequence taken with uncalibrated moving camera by integrating all frames in the sequence based on projective geometry between the frames. In this method, assuming that the object scene can be approximated with multiple plane patches, all frames in the input image sequence are registered with the fundament...

This paper deals with the problem of reconstruction from a sequence of images, by linear methods. The reconstruction is made directly, without calculating the fundamental matrices or the trilinear tensors. In a general setting it is shown that it is possible to do such a reconstruction of six points from four images up to a projective transformation. Furthermore, when more point matches are ava...

For linear di erential algebraic equations of tractability index the notion of the adjoint equation is analysed in full detail Its solvability is shown at the lowest possible smoothness The fundamental matrices of both equations are de ned and their relationships are characterized

The quadrifocal tensor which connects image measurements along 4 views is not yet well understood as its counterparts the fundamental matrix and the trifocal tensor. This paper establishes the structure of the tensor as an \epipolehomography" pairing