Stereo Correspondence Through Feature Grouping and Maximal Cliques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Matching by Discrete Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structural Matching in Computer Vision Using Probabilistic Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure and Motion from Line Segments in Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic line matching across views
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
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
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Spectral Technique for Correspondence Problems Using Pairwise Constraints
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Object Recognition in High Clutter Images Using Line Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
MSLD: A robust descriptor for line matching
Pattern Recognition
Image and Vision Computing
2D Line Matching Using Geometric and Intensity Data
AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 03
BRIEF: binary robust independent elementary features
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
EDLines: A real-time line segment detector with a false detection control
Pattern Recognition Letters
Unsupervised Learning for Graph Matching
International Journal of Computer Vision
ORB: An efficient alternative to SIFT or SURF
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
BRISK: Binary Robust invariant scalable keypoints
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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We present a line matching algorithm which utilizes both the local appearance of lines and their geometric attributes. To overcome the problem of segment fragmentation and geometric variation, we extract lines in the scale space. To depict the local appearance of lines, we design a novel line descriptor called Line Band Descriptor (LBD). To evaluate the pairwise geometric consistency, we define the pairwise geometric attributes between line pairs. Then we built a relational graph for candidate line matches and employ a spectral technique to solve this matching problem efficiently. The advantages of the proposed algorithm are as follows: (1) it is robust to image transformations because of the multi-scale line detection strategy; (2) it is efficient because the designed LBD descriptor is fast to compute and the appearance similarities reduce the dimension of the graph matching problem; (3) it is accurate even for low-texture images because of the pairwise geometric consistency evaluation.