# Automatic Calibration of a Multi-Camera System with Limited Overlapping Fields of View for 3D Surgical Scene Reconstruction

arXiv: https://arxiv.org/abs/2501.16221 · HTML: https://mlsanity.com/paper/2501.16221/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 28 references that are in the map.
- First posted on arXiv 27 Jan 2025.

## Builds on (most cited first, 5 of 5)

- [Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1611.08050/) (2016)
- [Global Structure-from-Motion Revisited](https://mlsanity.com/paper/2407.20219/) (2024)
- [Robotic Surgery With Lean Reinforcement Learning](https://mlsanity.com/paper/2105.01006/) (2021)
- [Creating a Digital Twin of Spinal Surgery: A Proof of Concept](https://mlsanity.com/paper/2403.16736/) (2024)
- [ST(OR)2: Spatio-Temporal Object Level Reasoning for Activity Recognition in the Operating Room](https://mlsanity.com/paper/2312.12250/) (2023)

## Built on by (most cited first, 4 of 4)

- [AutoCam: Hierarchical Path Planning for an Autonomous Auxiliary Camera in Surgical Robotics](https://mlsanity.com/paper/2505.10398/) (2025)
- [RocSync: Millisecond-Accurate Temporal Synchronization for Heterogeneous Camera Systems](https://mlsanity.com/paper/2511.14948/) (2025)
- [A Multi-View Pipeline and Benchmark Dataset for 3D Hand Pose Estimation in Surgery](https://mlsanity.com/paper/2601.15918/) (2026)
- [Geometry OR Tracker: Universal Geometric Operating Room Tracking](https://mlsanity.com/paper/2603.00560/) (2026)

## Abstract (arXiv)

The purpose of this study is to develop an automated and accurate external camera calibration method for multi-camera systems used in 3D surgical scene reconstruction (3D-SSR), eliminating the need for operator intervention or specialized expertise. The method specifically addresses the problem of limited overlapping fields of view caused by significant variations in optical zoom levels and camera locations. We contribute a novel, fast, and fully automatic calibration method based on the projection of multi-scale markers (MSMs) using a ceiling-mounted projector. MSMs consist of 2D patterns projected at varying scales, ensuring accurate extraction of well distributed point correspondences across significantly different viewpoints and zoom levels. Validation is performed using both synthetic and real data captured in a mock-up OR, with comparisons to traditional manual marker-based methods as well as markerless calibration methods. The method achieves accuracy comparable to manual, operator-dependent calibration methods while exhibiting higher robustness under conditions of significant differences in zoom levels. Additionally, we show that state-of-the-art Structure-from-Motion (SfM) pipelines are ineffective in 3D-SSR settings, even when additional texture is projected onto the OR floor. The use of a ceiling-mounted entry-level projector proves to be an effective alternative to operator-dependent, traditional marker-based methods, paving the way for fully automated 3D-SSR.