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The implementation of part of the ORB (Oriented FAST and Rotated BRIEF) pipeline. The ORB consists of the feature detector and feature descriptor that detect and describe reproducible and discriminative regions in an image. Those, in turn, can be matched between pairs of images for correspondence search, 3D reconstruction, and so on.
This is an example to find multiple objects in images that match a template using ORB and SIFT feature detection methods. Handles different scales and rotations.
6-week project at the Computer Vision Centre in Barcelona in which I collaborated with Master students to develop software tools for uploading art images, and automatically identifying, and matching the images to an art database.
Repository concerning a feature detector and tracker developed for the Computer Vision course of the master's degree in Computer Science at University of Trento
Feature Detection and Matching with SIFT, SURF, KAZE, BRIEF, ORB, BRISK, AKAZE and FREAK through the Brute Force and FLANN algorithms using Python and OpenCV