# ACSC: Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems

arXiv: https://arxiv.org/abs/2011.08516 · HTML: https://mlsanity.com/paper/2011.08516/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Nov 2020.

## Built on by (most cited first, 7 of 7)

- [Online,Target-Free LiDAR-Camera Extrinsic Calibration via Cross-Modal Mask Matching](https://mlsanity.com/paper/2404.18083/) (2024)
- [Semantic Segmentation of Fruits on Multi-sensor Fused Data in Natural Orchards](https://mlsanity.com/paper/2208.02483/) (2022)
- [Environment-Driven Online LiDAR-Camera Extrinsic Calibration](https://mlsanity.com/paper/2502.00801/) (2025)
- [P2O-Calib: Camera-LiDAR Calibration Using Point-Pair Spatial Occlusion Relationship](https://mlsanity.com/paper/2311.02413/) (2023)
- [CLAIM: Camera-LiDAR Alignment with Intensity and Monodepth](https://mlsanity.com/paper/2512.14001/) (2025)
- [DST-Calib: A Dual-Path, Self-Supervised, Target-Free LiDAR-Camera Extrinsic Calibration Network](https://mlsanity.com/paper/2601.01188/) (2026)
- [Accelerating Point Cloud Ground Segmentation: From Mechanical to Solid-State Lidars](https://mlsanity.com/paper/2408.10404/) (2024)

## Abstract (arXiv)

Recently, the rapid development of Solid-State LiDAR (SSL) enables low-cost and efficient obtainment of 3D point clouds from the environment, which has inspired a large quantity of studies and applications. However, the non-uniformity of its scanning pattern, and the inconsistency of the ranging error distribution bring challenges to its calibration task. In this paper, we proposed a fully automatic calibration method for the non-repetitive scanning SSL and camera systems. First, a temporal-spatial-based geometric feature refinement method is presented, to extract effective features from SSL point clouds; then, the 3D corners of the calibration target (a printed checkerboard) are estimated with the reflectance distribution of points. Based on the above, a target-based extrinsic calibration method is finally proposed. We evaluate the proposed method on different types of LiDAR and camera sensor combinations in real conditions, and achieve accuracy and robustness calibration results. The code is available at https://github.com/HViktorTsoi/ACSC.git .