# Click-Calib: A Robust Extrinsic Calibration Method for Surround-View Systems

arXiv: https://arxiv.org/abs/2501.01557 · HTML: https://mlsanity.com/paper/2501.01557/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 37 references that are in the map.
- First posted on arXiv 2 Jan 2025.

## Builds on (most cited first, 10 of 10)

- [Center-based 3D Object Detection and Tracking](https://mlsanity.com/paper/2006.11275/) (2020)
- [BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation](https://mlsanity.com/paper/2205.13542/) (2022)
- [WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving](https://mlsanity.com/paper/1905.01489/) (2019)
- [Surround-view Fisheye Camera Perception for Automated Driving: Overview, Survey and Challenges](https://mlsanity.com/paper/2205.13281/) (2022)
- [Research on the Application of Computer Vision Based on Deep Learning in Autonomous Driving Technology](https://mlsanity.com/paper/2406.00490/) (2024)
- [PSDet: Efficient and Universal Parking Slot Detection](https://mlsanity.com/paper/2005.05528/) (2020)
- [Enhanced Parking Perception by Multi-Task Fisheye Cross-view Transformers](https://mlsanity.com/paper/2408.12575/) (2024)
- [Holistic Parking Slot Detection with Polygon-Shaped Representations](https://mlsanity.com/paper/2310.11629/) (2023)
- [Parking Spot Classification based on surround view camera system](https://mlsanity.com/paper/2310.12997/) (2023)
- [Automatic Surround Camera Calibration Method in Road Scene for Self-driving Car](https://mlsanity.com/paper/2305.16840/) (2023)

## Abstract (arXiv)

Surround-View System (SVS) is an essential component in Advanced Driver Assistance System (ADAS) and requires precise calibrations. However, conventional offline extrinsic calibration methods are cumbersome and time-consuming as they rely heavily on physical patterns. Additionally, these methods primarily focus on short-range areas surrounding the vehicle, resulting in lower calibration quality in more distant zones. To address these limitations, we propose Click-Calib, a pattern-free approach for offline SVS extrinsic calibration. Without requiring any special setup, the user only needs to click a few keypoints on the ground in natural scenes. Unlike other offline calibration approaches, Click-Calib optimizes camera poses over a wide range by minimizing reprojection distance errors of keypoints, thereby achieving accurate calibrations at both short and long distances. Furthermore, Click-Calib supports both single-frame and multiple-frame modes, with the latter offering even better results. Evaluations on our in-house dataset and the public WoodScape dataset demonstrate its superior accuracy and robustness compared to baseline methods. Code is available at https://github.com/lwangvaleo/click_calib.