We propose a system to capture nearly synchronous frame streams from multiple and moving handheld mobiles that is suitable for dynamic object 3D reconstruction. Each mobile executes Simultaneous Localisation and Mapping on-board to estimate its pose, and uses a wireless communication channel to send or receive synchronisation triggers. Our system can harvest frames and mobile poses in real time using a decentralised triggering strategy and a data-relay architecture that can be deployed either at the Edge or in the Cloud. We show the effectiveness of our system by employing it for 3D skeleton and volumetric reconstructions. Our triggering strategy achieves equal performance to that of an NTP-based synchronisation approach, but offers higher flexibility, as it can be adjusted online based on application needs. We created a challenging new dataset, namely 4DM, that involves six handheld augmented reality mobiles recording an actor performing sports actions outdoors. We validate our system on 4DM, analyse its strengths and limitations, and compare its modules with alternative ones.

我们提出了一种用于捕获来自多个移动手持移动设备的几乎同步帧流的系统，该系统适用于动态对象3D重建。每个移动设备在板上执行“同时定位和映射”以估计其姿态，并使用无线通信信道发送或接收同步触发器。我们的系统可以使用分散式触发策略和可在Edge或Cloud中部署的数据中继架构实时捕获帧和移动姿势。通过将其用于3D骨架和体积重建，我们展示了系统的有效性。我们的触发策略可实现与基于NTP的同步方法相同的性能，但由于可以根据应用程序需求进行在线调整，因此具有更高的灵活性。我们创建了一个具有挑战性的新数据集，即4DM，其中涉及六个手持式增强现实手机，记录了一个演员在户外进行体育活动的情况。我们在4DM上验证我们的系统，分析其优势和局限性，并将其模块与其他模块进行比较。