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