The aim was to construct 3D sparse reconstruction of a scene using a set of unordered images.
- Conding was done on Python using the opencv library
- The visualisation was done on MeshLab
- Extract features between two images using fast features
- Estimate the relative pose of 2nd frame wrt 1.
- Triangulate common features found between two images to obtain 3D point.
- Append the point in a .ply file
- Repeat the above 4 steps for the series of images.
The dataset was taken from here The calibration matrix for the same can be ontained from the respective data.mat files