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
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparison of Affine Region Detectors
International Journal of Computer Vision
A MapReduce-based indoor visual localization system using affine invariant features
Computers and Electrical Engineering
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A new technical framework for remote sensing image matching by integrating affine invariant feature extraction and RANSAC is presented. The novelty of this framework is an automatic optimization strategy for affine invariant feature matching based on RANSAC. An automatic way to determine the distance threshold of RANSAC is proposed, which is a key problem to implement this RANSAC-based automatic optimization. Since affine invariant feature matching technology has been successfully applied to remote sensing image matching, we design an experiment to compare the proposed framework (with optimization) with the standard affine invariant feature matching (without optimization). By using three pairs with different types of imagery, the experimental results indicate that the proposed framework can always get higher correctness of image matching in automatic way, compared to the standard affine invariant feature matching technology.