Verlagslink DOI: | 10.1007/978-3-031-85187-2_21 10.48550/arXiv.2409.20127 |
Titel: | PuzzleBoard : a new camera calibration pattern with position encoding | Sonstige Titel: | PuzzleBoard : ein neues Kamerakalibriermuster mit Positionskodierung | Sprache: | Englisch | Autorenschaft: | Stelldinger, Peer ![]() Schönherr, Nils Biermann, Justus |
Herausgeber*In: | Cremers, Daniel Lähner, Zorah Moeller, Michael Nießner, Matthias Ommer, Björn Triebel, Rudolph |
Schlagwörter: | Calibration Pattern; Chessboard; Checkerboard; Fiducial Markers; PuzzleBoard | Erscheinungsdatum: | 24-Apr-2025 | Verlag: | Springer | Teil der Schriftenreihe: | Pattern Recognition : 46th DAGM German Conference, DAGM GCPR 2024, Munich, Germany, September 10–13, 2024, Proceedings, Part II | Zeitschrift oder Schriftenreihe: | Lecture notes in computer science | Zeitschriftenband: | 15298 | Konferenz: | The German Conference on Pattern Recognition (GCPR) and Symposium on Vision, Modeling, and Visualization (VMV) 2024 | Zusammenfassung: | Accurate camera calibration is a well-known and widely used task in computer vision that has been researched for decades. However, the standard approach based on checkerboard calibration patterns has some drawbacks that limit its applicability. For example, the calibration pattern must be completely visible without any occlusions. Alternative solutions such as ChArUco boards allow partial occlusions, but require a higher camera resolution due to the fine details of the position encoding. We present a new calibration pattern that combines the advantages of checkerboard calibration patterns with a lightweight position coding that can be decoded at very low resolutions. The decoding algorithm includes error correction and is computationally efficient. The whole approach is backward compatible to both checkerboard calibration patterns and several checkerboard calibration algorithms. Furthermore, the method can be used not only for camera calibration but also for camera pose estimation and marker-based object localization tasks. |
URI: | https://hdl.handle.net/20.500.12738/16528 | ISSN: | 1611-3349 | Begutachtungsstatus: | Diese Version hat ein Peer-Review-Verfahren durchlaufen (Peer Review) | Einrichtung: | Forschungs- und Transferzentrum Smart Systems Department Informatik Fakultät Technik und Informatik |
Dokumenttyp: | Konferenzveröffentlichung | Hinweise zur Quelle: | Preprint: https://doi.org/10.48550/arXiv.2409.20127. Verlagsversion: https://doi.org/10.1007/978-3-031-85187-2_21 |
Enthalten in den Sammlungen: | Publications without full text |
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