Title: Consensus-based Distributed Variational Multi-object Tracker in Multi-Sensor Network Show Chinese title

Title: 基于一致性分布式变分多目标跟踪器的多传感器网络

Abstract: The growing need for accurate and reliable tracking systems has driven significant progress in sensor fusion and object tracking techniques. In this paper, we design two variational Bayesian trackers that effectively track multiple targets in cluttered environments within a sensor network. We first present a centralised sensor fusion scheme, which involves transmitting sensor data to a fusion center. Then, we develop a distributed version leveraging the average consensus algorithm, which is theoretically equivalent to the centralised sensor fusion tracker and requires only local message passing with neighbouring sensors. In addition, we empirically verify that our proposed distributed variational tracker performs on par with the centralised version with equal tracking accuracy. Simulation results show that our distributed multi-target tracker outperforms the suboptimal distributed sensor fusion strategy that fuses each sensor's posterior based on arithmetic sensor fusion and an average consensus strategy. Show Chinese abstract

Abstract: 日益增长的对准确可靠的跟踪系统的需求推动了传感器融合和目标跟踪技术的重大进展。在本文中，我们设计了两种变分贝叶斯跟踪器，能够在传感器网络中的杂乱环境中有效跟踪多个目标。我们首先提出了一种中心化传感器融合方案，该方案涉及将传感器数据传输到融合中心。然后，我们开发了一种利用平均一致算法的分布式版本，该版本在理论上等同于中心化传感器融合跟踪器，并且只需要与邻近传感器进行本地消息传递。此外，我们通过实验证实所提出的分布式变分跟踪器与中心化版本具有相同的跟踪精度。仿真结果显示，我们的分布式多目标跟踪器优于基于算术传感器融合和平均一致策略的次优分布式传感器融合策略。