A collection of educational notebooks on multi-view geometry and computer vision.

Multiview notebooks

This is a collection of educational notebooks on multi-view geometry and computer vision. Subjects covered in these notebooks include:

• Camera calibration
• Perspective projection
• 3D point triangulation
• Quaternions as 3D pose representation
• Perspective-n-point (PnP) algorithm
• Levenberg–Marquardt optimization
• Epipolar geometry
• Relative 2nd cam pose from stereo views w. fundamental matrix
• Relative 2nd cam pose from stereo views w. homography
• Bundle adjustment
• Structure from motion

Note Notebook 5 is working but not as tidy as the rest (yet). This notebook covers the Faugeras method to infer relative pose from a homography.

How to run

The notebooks can be run in the browser by clicking the binder badge . If one is interested in running the notebooks locally, I highly recommend using Docker as there is a dependency on g2opy and ipyvolume, which are challenging to install.

# Builds the environment 
docker build -t multiview_notebooks .

# Start a jupyter lab which can be opened in the browser
docker run -it --rm -p 8888:8888 multiview_notebooks jupyter-lab --ip=0.0.0.0 --port=8888

After starting the jupyter lab, the notebooks can be found in the home directory.
For the source of the Dockerfile, see this repository

Examples of visualizations

For more examples, see this video on youtube