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P$^2$Calib: Utilizing Pattern Priors for LiDAR-Camera Extrinsic Calibration — arXiv:2609.07516

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.07516
License (as archived): CC0-1.0
Archived: 2026-10-16T15:31:10.027Z
SHA-256 of the archived text: 110fba9ab1fde5988aff52b10c80bf124bd8610422fb33762997dbe6e203e2d9
Stable URL of this page: https://metraipolis.com/documento/dc_1972eb37ded4

How to cite

P$^2$Calib: Utilizing Pattern Priors for LiDAR-Camera Extrinsic Calibration — arXiv:2609.07516 — arXiv (en), https://arxiv.org/abs/2609.07516 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_1972eb37ded4 (Metraipolis archive dc_1972eb37ded4, sha256 110fba9ab1fde5988aff52b10c80bf124bd8610422fb33762997dbe6e203e2d9)

BibTeX

@misc{dc1972eb37ded4,
  title = {P$^2$Calib: Utilizing Pattern Priors for LiDAR-Camera Extrinsic Calibration — arXiv:2609.07516},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.07516},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_1972eb37ded4; sha256 110fba9ab1fde5988aff52b10c80bf124bd8610422fb33762997dbe6e203e2d9},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.07516. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Target-based LiDAR-camera extrinsic calibration is a prerequisite for multi-sensor fusion in robotics. However, in the widely adopted four-hole pipeline, \rt{calibration accuracy is limited by hole-center extraction in the LiDAR side, where sparse angular coverage and mixed-pixel returns displace the estimated centers}. This paper presents P$^2$Calib, which exploits \textit{pattern priors}, geometric constraints specified by the CAD model of the target board, to improve calibration accuracy. First, we incorporate the known hole radius as a fitting constraint to prevent center estimates from degrading under sparse angular coverage. Building on the improved hole estimates, we further enforce the rigid rectangular layout of the four holes as a global consistency constraint to correct residual errors across holes. Both priors are integrated into an \rt{interactive tool that runs the pipeline from target detection to the final extrinsic}. Experiments on simulated and real datasets show that P$^2$Calib reduces the joint registration residual by 90\% and 82\% and the held-out reprojection error by 96\% and 77\% over the baseline. \rt{We will release the code and data\codelink{} to facilitate future research.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-09 in cs.RO).
Categorie arXiv: Robotics (cs.RO).
Pagina del lavoro: https://arxiv.org/abs/2609.07516 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-16T15:11:47.596Z dalla pagina https://arxiv.org/catchup/cs.RO/2026-09-09?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).