ORB Feature & Feature Matching

Date and Time

2021-05-14 3:00 오후

Place

22319 (on-line and off-line)

Speaker(s)

Hong-ryul Jung

Overview

1. Oriented FAST (oFAST) ___a. FAST ___b. Image Pyramid ___c. oFAST 2. Rotated BRIEF (rBRIEF) ___a. BRIEF ___b. Steered BRIEF ___c. rBRIEF 3. FLANN ___a. LSH / Multi-probe LSH ___b. KD Tree / Multiple Randomized KD Trees ___c. FLANN

YouTube

Reference(s)

[1] X. Gao, T. Zhang, Y. Liu, and Q. Yan, 14 Lectures on Visual SLAM: From Theory to Practice. Publishing House of Electronics Industry, 2017.
[2] Direct vs Feature-based SLAM. (Source: https://vision.in.tum.de/research/vslam/lsdslam)
[3] E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, “ORB: An efficient alternative to SIFT or SURF,” in 2011 International Conference on Computer Vision, Barcelona, Spain, Nov. 2011, pp. 2564–2571, doi: 10.1109/ICCV.2011.6126544.
[4] OpenCV Source Code: https://github.com/opencv/opencv_contrib/blob/master/modules/xfeatures2d/src/brief.cpp
[5] M. Calonder, V. Lepetit, C. Strecha, and P. Fua, “BRIEF: Binary Robust Independent Elementary Features,” in Computer Vision – ECCV 2010, Berlin, Heidelberg, 2010, pp. 778–792, doi: 10.1007/978-3-642-15561-1_56.
[6] Deepanshu Tyagi, “Introduction to ORB (Oriented FAST and Rotated BRIEF),” blog post url: https://medium.com/data-breach/introduction-to-orb-oriented-fast-and-rotated-brief-4220e8ec40cf
[7] M. Muja and D. Lowe, Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration., vol. 1. 2009, p. 340.
[8] Victor Lavrenko, “kNN.16 Locality sensitive hashing (LSH),” 2014, url: https://youtu.be/LqcwaW2YE_c
[9] FLANN GitHub source code, url: https://github.com/flann-lib/flann/blob/master/src/cpp/flann/defines.h
[10] D. Scaramuzza, “Lecture 04 Feature Extraction 2 – UZH,” University of Zurich (ETH zurich, Robotics & Percetion Group), Oct. 25, 2018, [Online]. Available: http://rpg.ifi.uzh.ch/.
[11] Victor Lavrenko, “LSH.9 Locality-sensitive hashing: how it works,” 2015, url: https://youtu.be/Arni-zkqMBA
[12] Presentation by Mohammad Sadegh Riazi, RICE Univ., “FLANN,” url: https://slideplayer.com/slide/5383891/
[13] OpenCV Feature Matching, url: https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_feature2d/py_matcher/py_matcher.html#flann-based-matcher

Seminar Material

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