Robust recovery of the epipolar geometry for an uncalibrated stereo rig
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Artificial Intelligence - Special volume on computer vision
Sequential Updating of Projective and Affine Structure from Motion
International Journal of Computer Vision
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
On accurate and robust estimation of fundamental matrix
Computer Vision and Image Understanding
Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Multiple view geometry in computer vision
Multiple view geometry in computer vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Nonlinear Estimation of the Fundamental Matrix with Minimal Parameters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Interest point detection using imbalance oriented selection
Pattern Recognition
Interest points of general imbalance
IEEE Transactions on Image Processing
Detecting image points of general imbalance
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A global-to-local scheme for imbalanced point matching
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A hybrid representation of imbalanced points for two-layer matching
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
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Estimation of fundamental matrices is important in 3D computer vision. It is well known that the estimation of fundamental matrices is sensitive to outliers-even a few of imprecise point correspondences may result in an estimated fundamental matrix inconsistent with the geometry setup of input images. In terms of interest points with localities, we have proposed a two-layer matching scheme that is a generalization of conventional normalized cross correlation (NCC), aiming to improve the precision of point correspondence. A locality of interest points means a set of interest points that are contiguous to each other in terms of 8-connectivity. The first layer of the matching scheme establishes locality correspondence, and the second layer refines point correspondence within matching localities. In this paper, we analyze a limitation of the similarity measure of localities proposed in our previous work and then we propose two new similarity measures to address the limitation. We test the two-layer matching scheme on images in Middlebury stereo datasets, with known fundamental matrices as the ground truth. From the experimental results, we observe the improvement of new measures of locality similarity, and we also observe that the estimated fundamental matrices are consistently close to the ground truth.