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.ipynb_checkpoints (0, 2019-06-05)
.ipynb_checkpoints\ORB- Feature Matcher-checkpoint.ipynb (2471001, 2019-06-05)
.vscode (0, 2019-06-05)
.vscode\settings.json (47, 2019-06-05)
MSD (0, 2019-06-05)
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# Oriented FAST and Rotated BRIEF based Feature Matching Oriented FAST and Rotated BRIEF (ORB) is basically a fusion of FAST keypoint detector and BRIEF descriptor with many modifications to enhance the performance. First it use FAST to find keypoints, then apply Harris corner measure to find top N points among them. It also use pyramid to produce multiscale-features. I will be using opencv-python for the implementation of the assignment and algorithm. Major advantages of the ORB: * Scale Invariance * Rotational Invariance * Illumination Invariance * Noise Invariance ## The final json is contained in file final_data.json ## Installing requirements. 1) python version 3.5.1 2) pip version 19.1.1 3) Preferred OS: Ubuntu 16.04 (tested) Now go to the directly and run the following command: >* pip install -r requirements.txt ## Running the code The final code lies in the file get_json.py For step wise understanding the ORB code please check: ORB- Feature Matcher So just run the file to get the output as final_data.json ## Code details The algorithm is majorly implemented in file feature_match.py, which contain the feature matching orb algorithm and also the outlier removal code. For more insight into code implementation, please check the assignment report Report

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