A sample ORB vocabulary file can be downloaded from here https://drive.google.com/open?id=1wUPb328th8bUqhOk-i8xllt5mgRW4n84

https://github.com/xdspacelab/openvslam

AKAZE Fast explicit diffusion for accelerated features in nonlinear scale spaces, P.F. Alcantarilla, J. Nuevo, A. Bartoli, 2013

A comparative analysis of SIFT, SURF, KAZE, AKAZE, ORB, and BRISK

Akaze_liop: Wang, Z., Fan, B., Wu, F.: Local intensity order pattern for feature description. In: IEEE International Conference on Computer Vision (ICCV). pp.603–610 (2011)

Feature Evaluation with High-Resolution Images

general overview

Introduction to SIFT

SIFT explained

ORB (Oriented FAST and Rotated BRIEF)

http://www.willowgarage.com/sites/default/files/orb_final.pdf

https://medium.com/analytics-vidhya/introduction-to-orb-oriented-fast-and-rotated-brief-4220e8ec40cf

ORB: an efficient alternative to SIFT or SURF (with/without cuda)

https://www.researchgate.net/publication/221111151_ORB_an_efficient_alternative_to_SIFT_or_SURF

Harris Corner Detector

https://medium.com/analytics-vidhya/introduction-to-harris-corner-detector-32a88850b3f6

https://docs.opencv.org/3.4/dc/d0d/tutorial_py_features_harris.html

https://in.udacity.com/course/computer-vision-nanodegree--nd891

http://aishack.in/tutorials/harris-corner-detector/

SIFT (Scale Invariant Feature Transform)

https://medium.com/analytics-vidhya/introduction-to-sift-scale-invariant-feature-transform-65d7f3a72d40

https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_feature2d/py_sift_intro/py_sift_intro.html

https://in.udacity.com/course/computer-vision-nanodegree--nd891

http://aishack.in/tutorials/sift-scale-invariant-feature-transform-introduction/

SURF (Speeded-Up Robust Features)

https://medium.com/analytics-vidhya/introduction-to-surf-speeded-up-robust-features-c7396d6e7c4e

https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_feature2d/py_surf_intro/py_surf_intro.html

https://in.udacity.com/course/computer-vision-nanodegree--nd891

https://www.vision.ee.ethz.ch/~surf/eccv06.pdf

http://eric-yuan.me/surf/

FAST (Features from Accelerated Segment Test)

https://medium.com/analytics-vidhya/introduction-to-fast-features-from-accelerated-segment-test-4ed33dde6d65

Viswanathan, Deepak. “Features from Accelerated Segment Test ( FAST ).” (2011).

Edward Rosten and Tom Drummond, “Machine learning for high speed corner detection” in 9th European Conference on Computer Vision, vol. 1, 2006, pp. 430–443.

Edward Rosten, Reid Porter, and Tom Drummond, “Faster and better: a machine learning approach to corner detection” in IEEE Trans. Pattern Analysis and Machine Intelligence, 2010, vol 32, pp. 105–119.

https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_feature2d/py_fast/py_fast.html

https://in.udacity.com/course/computer-vision-nanodegree--nd891

BRIEF(Binary Robust Independent Elementary Features)

Binary robust independentelementary features

https://www.researchgate.net/publication/221304115_BRIEF_Binary_Robust_Independent_Elementary_Features

https://medium.com/analytics-vidhya/introduction-to-brief-binary-robust-independent-elementary-features-436f4a31a0e6

https://docs.opencv.org/3.1.0/dc/d7d/tutorial_py_brief.html

https://in.udacity.com/course/computer-vision-nanodegree--nd891

https://gilscvblog.com/2013/09/19/a-tutorial-on-binary-descriptors-part-2-the-brief-descriptor/

DBRIEF

Efficient Discriminative Projectionsfor Compact Binary Descriptors

https://www.labri.fr/perso/vlepetit/pubs/trzcinski_eccv12.pdf

BRISK

Brisk: Binary robust invariant scalablekeypoints

https://www.researchgate.net/publication/221110715_BRISK_Binary_Robust_invariant_scalable_keypoints

FREAK

FREAK: Fast retina keypoint

https://www.researchgate.net/publication/258848394_FREAK_Fast_retina_keypoint

BinBoost

Boosting Binary Keypoint Descriptors

https://www.researchgate.net/publication/261259229_Boosting_Binary_Keypoint_Descriptors

Learning Image Descriptors with Boosting

https://www.tugraz.at/fileadmin/user_upload/Institute/ICG/Images/team_lepetit/publications/trzcinski_pami15.pdf

LDAHash

LDAHash: Improved matching with smallerdescriptors

https://wiki.epfl.ch/edicpublic/documents/Candidacy%20exam/LDAHash.pdf

LATCH

LATCH: learned arrangements of three patch codes. In:Winter Conf. on Applications of Comput.

https://talhassner.github.io/home/publication/2016_WACV_2

CLATCH

Fastest implementation of the fully scale- and rotation-invariant LATCH 512-bit binary feature descriptor as described in the 2015 paper by Levi and Hassner

https://github.com/komrad36/CLATCH

https://talhassner.github.io/home/projects/LATCH/CLATCH_ECCV2016.pdf

License: ask author