mlsanityData to 14 Oct 2026

SceneCalib: Automatic Targetless Calibration of Cameras and Lidars in Autonomous Driving

arXiv 2304.05530 ↗First posted 11 Apr 2023cs.CVcited by 2

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Abstract (arXiv)

Accurate camera-to-lidar calibration is a requirement for sensor data fusion in many 3D perception tasks. In this paper, we present SceneCalib, a novel method for simultaneous self-calibration of extrinsic and intrinsic parameters in a system containing multiple cameras and a lidar sensor. Existing methods typically require specially designed calibration targets and human operators, or they only attempt to solve for a subset of calibration parameters. We resolve these issues with a fully automatic method that requires no explicit correspondences between camera images and lidar point clouds, allowing for robustness to many outdoor environments. Furthermore, the full system is jointly calibrated with explicit cross-camera constraints to ensure that camera-to-camera and camera-to-lidar extrinsic parameters are consistent.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 6 of its 33 references that are in the map. First posted on arXiv 11 Apr 2023.

Builds on

6 of 33 references.

References · 6

  1. 2015ORB-SLAM: a Versatile and Accurate Monocular SLAM Systemcited by 988
  2. 2021Pixel-level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environmentscited by 49
  3. 2021CRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road Scenescited by 19
  4. 2020Spatiotemporal Camera-LiDAR Calibration: A Targetless and Structureless Approachcited by 15
  5. 2019Road is Enough! Extrinsic Calibration of Non-overlapping Stereo Camera and LiDAR using Road Informationcited by 6
  6. 2022TEScalib: Targetless Extrinsic Self-Calibration of LiDAR and Stereo Camera for Automated Driving Vehicles with Uncertainty Analysiscited by 2

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Citing papers per year: 2024: 1; 2025: 1.

2 papers.