Stereo vision is essential for many applications. Currently, the synchronization of the streams coming from two cameras is done using mostly hardware. A software-based synchronization method would reduce the cost, weight and size of the entire system and allow for more flexibility when building such systems. With this goal in mind, we present here a comparison of different deep learning-based systems and prove that some are efficient and generalizable enough for such a task. This study paves the way to a production ready software-based video synchronization system.
@article{arxiv.2303.12916,
title = {Deep learning-based stereo camera multi-video synchronization},
author = {Nicolas Boizard and Kevin El Haddad and Thierry Ravet and François Cresson and Thierry Dutoit},
journal= {arXiv preprint arXiv:2303.12916},
year = {2023}
}