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The estimation of fundamental matrix is a key problem in computer vision and also the basis of active vision. A new linear iterative algorithm for estimating the fundamental matrix has been presented. The algorithm is based on minimizing the actual distances between the projection points and their matched epipolar lines. The first two fundamental matrixes are computed with the information of images...
Rectification of stereo vision is also call rectification of Epipolar Lines. For searching the corresponding points rapidly and accurately, the rectification is used to make the epipolar lines of stereo images be parallel to the horizontal direction and remove the parallax in vertical direction. In the paper, a robust algorithm is presented to rectify the stereo images based on the traditional projective...
In this paper, we consider the problem of estimating the spatiotemporal alignment between N unsynchronized video sequences of the same dynamic 3D scene, captured from distinct viewpoints. Unlike most existing methods, which work for N = 2 and rely on a computationally intensive search in the space of temporal alignments, we present a novel approach that reduces the problem for general N to the robust...
The Orthogonal Iteration (OI) algorithm for pose estimation from point correspondences is global convergent, efficient and robust, which make this algorithm quite attractive. In this paper, we extend the OI algorithm to 2D-3D line correspondences and present an iterative algorithm referred to as LBOI (Line-Based Orthogonal Iterative Algorithm). We first derive a new form of fundamental equations and...
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