Automatic Panorama Stitching

Theoretical (Analytical):

Practical (Implementation):

Literature Work:


Soccer tracking is often performed using multi-camera systems. Multi-Camera Panorama stitching is a common method for generating high-resolution video, which serves as the basis for the tracking. Additionally, projection of the stitched video into a single image plane is often accompanied by image distortion, which might cause problems and reduce the tracking quality.

Problem Statement

  • Merging of low-overlap videos is often done manually or semi-automatically.
  • Distortion degrades the quality of further computer vision methods  
  • It is desirable to identify distortion-minimizing projection methods


  • Implement automatic alignment and calibration of camera parameters from low-overlap videos
  • (Optional) automatic estimation of lens distortion parameters
  • Evaluation of different projection methods for the mapping between camera views and the output video with a focus on minimizing distortion of the input videos
  • Evaluation of the application potential of the researched methods as well as potential future work towards a completely automatic stitching and reprojection method


  • Good Python and OpenCV skills
  • Basic knowledge in computer vision fundamentals
  • (Optional): Basic knowledge about deep learning models



  • Scope: Bachelor/Master
  • 3 Month Project, 3/6 Month Thesis
  • Start: immediately