A comprehensive tutorial series on Image Formation and Camera Calibration in Python with example

Setting up

Assuming you've anaconda installed, create a virtual environment and install dependencies.

Create Virtual Environment

conda create -n camera-calibration-python python=3.6 anaconda
conda activate camera-calibration-python

Clone and Install dependencies

git clone https://github.com/wingedrasengan927/Image-formation-and-camera-calibration.git
cd Image-formation-and-camera-calibration
pip install -r requirements.txt

There are two main libraries we'll be using:
pytransform3d: This library has great functions for visualizations and transformations in the 3D space.
ipympl: It makes the matplotlib plot interactive allowing us to perform pan, zoom, and rotation in real time within the notebook which is really helpful when working with 3D plots.

Note: If you're using Jupyter Lab, please install the Jupyter Lab extension of ipympl from here

ipympl can be accessed in the notebook by including the magic command %matplotlib widget

Contents

Part 1: Image Formation and Pinhole Model of the Camera
Here we discuss pinhole model of the camera and image formation. We also give an overview of camera extrinsics, camera intrinsics, and camera calibration.

Part 2: Camera Extrinsics in Python
Here we discuss camera extrinsic matrix in depth including change of basis and linear transformation in rotation and translation.

Part 3: Camera Intrinsics in Python
Here we discuss camera intrinsic matrix, and the projection transformation of the points from camera coordinate system to the image plane of the camera.

Part 4: Positive Definite Matrices and Ellipsoids
Here we discuss the properties of positive definite matrices which we'll later use in camera calibration.

Part 5: Camera Calibration in Python
Here we discuss the different methods of camera calibration in python with examples.