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Testing various detector / descriptor combinations to see which ones perform best to be used in a collision detection system. Also 2 different approaches (FLANN vs. Brute-force with the descriptor distance ratio test) for keypoints matching are tested.
This is an assignment for our computer vision course. It uses py-Qt5 to make GUI and open-cv to detect feature points and match them. Finally, it outputs an image which is stitched by two images. Part of this code comes from the Internet. Thanks for their unselfish dedication.
The idea of the camera course is to build a collision detection system. You will now build the feature tracking part and test various detector / descriptor combinations to see which ones perform best.