Estimating the Fundamental Matrix via Constrained Least-Squares: A Convex Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Content-Based Image Retrieval Based on Local Affinely Invariant Regions
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
What Do Features Tell about Images?
Scale-Space '01 Proceedings of the Third International Conference on Scale-Space and Morphology in Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
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
Histograms of Oriented Gradients for Human Detection
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
Simultaneous Object Recognition and Segmentation from Single or Multiple Model Views
International Journal of Computer Vision
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
A 3-dimensional sift descriptor and its application to action recognition
Proceedings of the 15th international conference on Multimedia
Scene Classification Using a Hybrid Generative/Discriminative Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Fundamental matrix estimation: A study of error criteria
Pattern Recognition Letters
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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This paper presents a novel method for addressing the problem of finding more good feature pairs between images, which is one of the most fundamental tasks in computer vision and pattern recognition. We first select matched features by Bi-matching as seed points, then organize these seed points by adopting the Delaunay triangulation algorithm. Finally, triangle constraint is used to explore good matches. The experimental evaluation shows that our method is robust to most geometric and photometric transformations including rotation, scale change, blur, viewpoint change, JPEG compression and illumination change, and significantly improves both the number of correct matches and the matching score. And the application on estimating the fundamental matrix for a pair of images is also shown. Both the experiments and the application demonstrate the robust performance of our method.