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ClearLines - Camera Calibration from Straight Lines

arXiv 2505.00452 ↗First posted 1 May 2025cs.CVcited by 0

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Abstract (arXiv)

The problem of calibration from straight lines is fundamental in geometric computer vision, with well-established theoretical foundations. However, its practical applicability remains limited, particularly in real-world outdoor scenarios. These environments pose significant challenges due to diverse and cluttered scenes, interrupted reprojections of straight 3D lines, and varying lighting conditions, making the task notoriously difficult. Furthermore, the field lacks a dedicated dataset encouraging the development of respective detection algorithms. In this study, we present a small dataset named "ClearLines", and by detailing its creation process, provide practical insights that can serve as a guide for developing and refining straight 3D line detection algorithms.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 37 references that are in the map. First posted on arXiv 1 May 2025.

Builds on

6 of 37 references.

References · 6

  1. 2019Why Having 10,000 Parameters in Your Camera Model is Better Than Twelvecited by 43
  2. 2022TVCalib: Camera Calibration for Sports Field Registration in Soccercited by 22
  3. 2019Optimizing Through Learned Errors for Accurate Sports Field Registrationcited by 19
  4. 2024A Universal Protocol to Benchmark Camera Calibration for Sportscited by 14
  5. 2021Recalibrating the KITTI Dataset Camera Setup for Improved Odometry Accuracycited by 9
  6. 2024Interaction of Autonomous and Manually Controlled Vehicles Multiscenario Vehicle Interaction Datasetcited by 5

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