Distributed Cooperative Estimation for Visual Sensor Networks

本计画的目标是建立一个智慧型网路系统，透过分散式资讯处理与决策，以视觉感测网路来估测目标的运动。视觉感测网路是由多个智慧型摄影机所组成，具有通讯与运算能力。首先，我们提出了一个分布式合作的视觉估计机制，称为网络视觉运动观测器，结合两个不同的以前的工作：基于被动的视觉运动观测器和基于被动的姿态同步控制。所提出的估计机制通过视觉运动观测器执行局部估计，并基于同步技术聚合相邻相机的估计。然后，我们澄清了一个平均性能的估计所提出的机制的基础上，分布式优化和姿势同步技术。对目标运动与平均性能之间的关系进行了理论分析。此外，我们建立了一个实际的视觉传感器网络系统，并证明了所提出的理论结果的有效性。最后，我们量化了恶意传感器和不完美的可见性对平均性能的影响，并改进了传感器网络系统，使其即使在存在此类不良事件的情况下也能正常工作。

The goal of this project is to establish a smart network system estimating target motion via distributed information processing and decision-making for a visual sensor network which is a network consisting of multiple smart cameras with communication and computation capability. We first presented a distributed cooperative visual estimation mechanism, called networked visual motion observer, by combining two different previous works: a passivity-based visual motion observer and passivity-based pose synchronization control. The proposed estimation mechanism executes local estimation via the visual motion observer and aggregates the neighboring cameras estimates based on the synchronization techniques. Then, we clarified an averaging performance of the estimates produced by the proposed mechanism based on the techniques in distributed optimization and pose synchronization. We also conducted theoretical analysis on a relation between target motion and the averaging performance. In addition, we built an actual visual sensor network system and demonstrated validity of the presented theoretical results. Finally, we quantified the effects of malicious sensors and imperfect visibility on the averaging performance and improved the sensor network system so that it works even in the presence of such undesirable events.