Potential of SIFT, SURF, KAZE, AKAZE, ORB, BRISK, AGAST, and 7 More Algorithms for Matching Extremely Variant Image Pairs
Author:
Affiliation:
1. Pakistan Navy Engineering College (PNEC) National University of Sciences and Technology (NUST),Karachi,Pakistan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10099038/10099054/10099250.pdf?arnumber=10099250
Reference33 articles.
1. A comparison of feature descriptors for visual SLAM
2. When to use what feature? SIFT, SURF, ORB, or A-KAZE features for monocular visual odometry
3. Speeded-Up Robust Features (SURF)
4. Distinctive Image Features from Scale-Invariant Keypoints
5. Image matching using local symmetry features
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