Camera to GPS calibration for trains using maps

In this project, we aim to create a camera map overlay, which various downstream vision applications require. Typically, a GPS-​to-camera calibration uses calibration aids and a particular procedure. In the field or with existing datasets, those are typically unavailable. We aim to develop a calibration procedure based on visual cues and available map information. The challenges lie in integrating infrastructure measurement into an optimization framework and temporally consistent sensor fusion.

• Review of literature on extrinsic calibration.
• Familiarization with existing code and work in this field.
• Development of a continuous calibration and reprojection pipeline.
• Testing and evaluation using recorded or simulated datasets.

• Highly motivated and independent student.
• Interest in SLAM and sensor fusion.
• Programming skills in Python or C++.
• Experience with computer vision frameworks is a plus.
• Enrolled at ETH Zurich.

If you are interested, please send your CV, Transcript of Records and a short paragraph explaining your motivation for the project to: cornelius.voneinem@mavt.ethz.ch, david.hug@mavt.ethz.ch, rik.baehnemann@mavt.ethz.ch