Python solution for project 3: CMSC733 Computer vision course.

In this project, we reconstructed a 3D scene and simultaneously obtained the camera poses with respect to the scene, with a given set of 6 images from a monocular camera and their feature point correspondences. Following are the steps involved:

• Feature detection and finding correspondences
• Estimating Fundamental Matrix
• Essential Matrix and solving for camera poses
• Linear Triangulation and recovering correct pose
• Non Linear Triangulation
• Linear PnP, RANSAC and Non linear optimization
• Bundle Adjustment

Please refer the report for detailed steps.

• Change the directory to the folder where Wrapper.py is located. Eg.

cd ./Code 

• Run the .py file using the following command:

python3 Wrapper.py --DataPath ./Data/

• --DataPath: the path where the data is stored
• --savepath: the path to folder where the output will be saved
• --BA: True-If we want to use bundle adjustment