Bachelor Thesis - Benchmarking Reconstruction Pipelines for Camera-to-Camera Calibration (m/f/d)

Bachelor Thesis - Benchmarking Reconstruction Pipelines for Camera-to-Camera Calibration (m/f/d)

Full time

Location: Saalburg-Ebersdorf | Jena

This thesis compares classical and learning-based 3D reconstruction pipelines for camera-to-camera extrinsic calibration on vehicle data. COLMAP will serve as the classical baseline, while selected learned reconstruction methods can be evaluated as alternatives. The goal is to identify which methods are suitable for different camera setups, environments, and recording conditions.

Your Role

• Prepare controlled calibration recordings and real-world vehicle datasets for evaluation.
• Run COLMAP and selected learned reconstruction pipelines.
• Compare calibration accuracy, robustness, and failure cases.
• Analyze the influence of texture, camera overlap, lighting, and dynamic objects.
• Document practical limitations and provide recommendations for future calibration workflows.

Required Qualifications

• Good programming skills in Python.
• Interest in computer vision and automated driving.
• Familiarity with Linux-based development environments.
• Basic understanding of cameras and image processing.

Preferred Qualifications

• First experience with COLMAP or similar 3D reconstruction tools.
• Interest in experimental evaluation and benchmarking.
• Basic knowledge of camera calibration or 3D reconstruction.

Benefits

• Work‑Life‑Balance: Flexible working hours and mobile working options.
• Ergonomic Workstations: Equipped with height‑adjustable desks and ergonomic office chairs.
• Company Events: Regular team events, meet & greets, and an annual Christmas party as integral parts of our company culture.
• Free Drinks: Enjoy complimentary coffee, tea, and water to keep you refreshed throughout the day.

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