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SCALABLE MULTI-CONSISTENCY FEATURE MATCHING WITH NON-COOPERATIVE GAMES (ICIP 2018)


This repository is a reference implementation for Chen Zhao, Jiaqi Yang, Yang Xiao and Zhiguo Cao, "SCALABLE MULTI-CONSISTENCY FEATURE MATCHING WITH NON-COOPERATIVE GAMES", ICIP 2018.

Citation


If you find our work useful in your research, please consider citing:

@inproceedings{zhao2018scalable,
    title={Scalable Multi-Consistency Feature Matching with Non-Cooperative Games},
	author={Zhao, Chen and Yang, Jiaqi and Xiao, Yang and Cao, Zhiguo},
	booktitle={Proceedings of the IEEE International Conference on Image Processing},
	pages={1258--1262},
	year={2018},
	organization={IEEE}
}

Usage


Run: Gird-GTM.exe “file_path“  “img_l” “img_r”

file_path: the path of the images.
img_l: the name of the left image.
img_r: the name of the right image.

Dataset


1affine.txt: affine informations around key-points in the left image.
1des.txt: descriptors in the left image.
1key_location.txt: positions of key-points in the left images, where the first line is the number of key-points.
2affine.txt: affine informations around key-points in the right image. 2des.txt”: descriptors in the right image.
2key_location.txt: positions of key-points in the right images, where the first line is the number of key-points.
match_idx.txt: key-point indexes of matching pairs.
gt_location.txt: positions of ground-truth inliers, where the first line is the number of inliers.

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