Trinocular Stereo Vision for Robotics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Projective Reconstruction and Invariants from Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
Theory and Practice of Projective Rectification
International Journal of Computer Vision
A compact algorithm for rectification of stereo pairs
Machine Vision and Applications
A new image rectification algorithm
Pattern Recognition Letters
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Navigation using Affine Structure from Motion
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Cylindrical rectification to minimize epipolar distortion
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Epipole and fundamental matrix estimation using virtual parallax
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Nonlinear Estimation of the Fundamental Matrix with Minimal Parameters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Applications of a direct algorithm for the rectification of uncalibrated images
Information Sciences—Informatics and Computer Science: An International Journal
Acquisition of translational motion by the parallel trinocular
Information Sciences: an International Journal
Stereo effect of image converted from planar
Information Sciences: an International Journal
Projective rectification from the fundamental matrix
Image and Vision Computing
Stereo rectification of uncalibrated and heterogeneous images
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Epipolar line estimation and rectification for stereo image pairs
IEEE Transactions on Image Processing
Weak convergence for random weighting estimation of smoothed quantile processes
Information Sciences: an International Journal
Hi-index | 0.07 |
Fundamental Matrix, or F-Matrix, is one of the most important and elemental tools in the field of computer vision. In conventional methods for estimating the F-Matrix, an eight-point algorithm is adopted. First, an approximate F-Matrix is calculated by a linear solver using at least eight corresponding pairs. Since this linear optimization method excludes an essential property, the rank 2 constraint, a method based on a singular value decomposition (SVD) is applied to impose the constraint. This last step with SVD, however, provides additional noise in the F-Matrix. Several methods introduce parameterizations taking into account the rank 2 constraint and optimized nonlinearly without SVD. In this paper, we propose a novel parameterization for the nonlinear optimization which includes this constraint. We adopt double quaternion (DQ) and a scalar as the parameter set. Experimental results show that the nonlinear optimization with our parameterization is competitive with other parameterization methods. Moreover, through the proposed parameterization, we can obtain two transformations for the two input images. These transformations lead to a novel method to estimate epipolar lines and to rectify the image pairs. This rectification method can deal with any image pairs in the same manner whether the epipoles are inside or outside the images.