Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Guided Sampling and Consensus for Motion Estimation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
A Computational Model for Periodic Pattern Perception Based on Frieze and Wallpaper Groups
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Matching with PROSAC " Progressive Sample Consensus
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Generalized RANSAC Framework for Relaxed Correspondence Problems
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Balanced Exploration and Exploitation Model Search for Efficient Epipolar Geometry Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Detecting large repetitive structures with salient boundaries
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Handling urban location recognition as a 2D homothetic problem
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Combining geometric and appearance priors for robust homography estimation
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Discovering texture regularity as a higher-order correspondence problem
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Structure from motion for scenes with large duplicate structures
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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Algorithms for the estimation of epipolar geometry from a pair of images have been very successful in recent years, being able to deal with wide baseline images. The algorithms succeed even when the percentage of correct matches from the initial set of matches is very low. In this paper the problem of scenes with repeated structures is addressed, concentrating on the common case of building facades. In these cases a large number of repeated features is found and can not be matched initially, causing state-of-the-art algorithms to fail. Our algorithm therefore clusters similar features in each of the two images and matches clusters of features. From these cluster pairs, a set of hypothesized homographies of the building facade are generated and ranked mainly according the support of matches of non-repeating features. Then in a separate step the epipole is recovered yielding the fundamental matrix. The algorithm then decides whether the fundamental matrix has been recovered reliably enough and if not returns only the homography. The algorithm has been tested successfully on a large number of pairs of images of buildings from the benchmark ZuBuD database for which several state-of-the-art algorithms nearly always fail.