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
Computer Vision and Image Understanding
International Journal of Computer Vision - 1998 Marr Prize
Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
International Journal of Computer Vision
New Techniques for Automated Architectural Reconstruction from Photographs
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Automatic line matching across views
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Multiple-View Structure and Motion From Line Correspondences
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Wide-Baseline Stereo Matching with Line Segments
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
3D from Line Segments in Two Poorly-Textured, Uncalibrated Images
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Towards Urban 3D Reconstruction from Video
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
MSLD: A robust descriptor for line matching
Pattern Recognition
Image matching by multiscale oriented corner correlation
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
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This paper presents a novel line matching method based on the intersection context of coplanar line pairs. The proposed method is designed to be especially effective for dealing with poorly structured and/or textured scenes. To overcome the ambiguity in line matching based on single line segments, the intersecting line pairs in 2D images that are coplanar in 3D are chosen instead for use in matching. The coplanarity of intersecting line pairs and their corresponding intersection context discriminate the true intersecting line pairs from the false intersecting ones in 3D. Compared to previous approaches, the method proposed herein offers efficient yet robust matching performance under poor line topologies or junction structures, while simultaneously estimating unknown camera geometry. This is due to the fact that the proposed method neither resorts to comprehensive topological relations among line segments nor relies on the presence of well-defined junction structures. The intersecting line pairs, used here as matching features, are more informative than the single line segments and simpler than the comprehensive topological relations. Also, the coplanarity criteria are more generally applied than the requirement of junction structures. Comparison studies and experimental results prove the accuracy and speed of the proposed method for various real world applications.