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2D Feature Tracking project using OpenCV detectors and descriptors for keypoint tracking in multiple frames. The project uses a variety of detectors and descriptors and performs analysis of the best possible combination with regards to processing time and detection precision.
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.
An algorithm for creating panoramic views from sequential images using computer vision techniques such as keypoints extraction, matching, and image alignment. Made in Python along with OpenCV and NumPy.
Multiview matching with deep-learning and hand-crafted local features for COLMAP and other SfM software. Supports high-resolution formats and images with rotations. Both CLI and GUI are supported.