Event-based cameras are increasingly utilized in various applications, owing to their high temporal resolution and low power consumption. However, a fundamental challenge arises when deploying multiple such cameras: they operate on independent time systems, leading to temporal misalignment. This misalignment can significantly degrade performance in downstream applications. Traditional solutions, which often rely on hardware-based synchronization, face limitations in compatibility and are impractical for long-distance setups. To address these challenges, we propose a novel algorithm that exploits the motion of objects in the shared field of view to achieve millisecond-level synchronization among multiple event-based cameras. Our method also concurrently estimates extrinsic parameters. We validate our approach in both simulated and real-world indoor/outdoor scenarios, demonstrating successful synchronization and accurate extrinsic parameters estimation.

翻译：事件相机因其高时间分辨率和低功耗特性，在诸多应用中日益广泛。然而，部署多台此类相机时面临一个根本性挑战：它们运行在独立的时间系统上，导致时间失准。这种失准会严重降低下游应用性能。传统解决方案通常依赖硬件同步，存在兼容性限制且不适用于长距离场景。为应对这些挑战，我们提出了一种新颖算法，利用共享视野中物体的运动实现多台事件相机间的毫秒级同步。我们的方法还能同时估计外部参数。我们在仿真及真实室内外场景中验证了该方法，成功实现了同步与精确的外部参数估计。