# On the Two-View Geometry of Unsynchronized Cameras

arXiv: https://arxiv.org/abs/1704.06843 · HTML: https://mlsanity.com/paper/1704.06843/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2017.

## Built on by (most cited first, 9 of 9)

- [Optimizing Elimination Templates by Greedy Parameter Search](https://mlsanity.com/paper/2203.14901/) (2022)
- [Spatiotemporal Multi-Camera Calibration using Freely Moving People](https://mlsanity.com/paper/2502.12546/) (2025)
- [Sparse resultant based minimal solvers in computer vision and their connection with the action matrix](https://mlsanity.com/paper/2301.06443/) (2023)
- [Automatic Solver Generator for Systems of Laurent Polynomial Equations](https://mlsanity.com/paper/2307.00320/) (2023)
- [AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications](https://mlsanity.com/paper/2501.10396/) (2024)
- [3D Trajectory Reconstruction of Moving Points Based on Asynchronous Cameras](https://mlsanity.com/paper/2506.00541/) (2025)
- [RocSync: Millisecond-Accurate Temporal Synchronization for Heterogeneous Camera Systems](https://mlsanity.com/paper/2511.14948/) (2025)
- [Visual Sync: Multi-Camera Synchronization via Cross-View Object Motion](https://mlsanity.com/paper/2512.02017/) (2025)
- [3D Reconstruction from public webcams](https://mlsanity.com/paper/2108.09476/) (2021)

## Abstract (arXiv)

We present new methods for simultaneously estimating camera geometry and time shift from video sequences from multiple unsynchronized cameras. Algorithms for simultaneous computation of a fundamental matrix or a homography with unknown time shift between images are developed. Our methods use minimal correspondence sets (eight for fundamental matrix and four and a half for homography) and therefore are suitable for robust estimation using RANSAC. Furthermore, we present an iterative algorithm that extends the applicability on sequences which are significantly unsynchronized, finding the correct time shift up to several seconds. We evaluated the methods on synthetic and wide range of real world datasets and the results show a broad applicability to the problem of camera synchronization.