Computer Vision and Photogrammetry Assignments

Overview

This repository contains academic assignments and resources for the course "Computer Vision and Photogrammetry." The materials focus on practical implementations of key concepts such as camera calibration, projection matrix calculation, and homography estimation using Python and MATLAB.

Folder Structure

• affine-2D-reconstruction/: Scripts and documentation for affine 2D reconstruction tasks.
• projection-matrix-calc/: Notebooks and MATLAB scripts for camera projection matrix calculation and decomposition.
• homography-matrix-calc/: Notebooks and images for homography matrix calculation and visualization.

Contents

• Jupyter notebooks with step-by-step implementations and visualizations.
• MATLAB scripts for advanced matrix operations and decompositions.
• Example images and output files for practical demonstrations.
• PDF reports documenting methodology, results, and analysis for each assignment.

Usage

1. Review the notebooks for Python-based implementations and visualizations.
2. Use MATLAB scripts for matrix decomposition and related tasks.
3. Refer to the PDF reports for detailed explanations and results.

Requirements

• Python: numpy, pandas, matplotlib, seaborn, opencv-python, scipy
• MATLAB: Standard environment

Author

Nikolaos Tsopanidis

License

See LICENSE file for details.