基于分布式压缩感知的无线视觉传感器网络多视点信息有效获取相关机制研究

项目名称： 基于分布式压缩感知的无线视觉传感器网络多视点信息有效获取相关机制研究

项目编号： No.61202380

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 计算机科学学科

项目作者： 由磊

作者单位： 天津大学

项目金额： 26万元

中文摘要： 无线视觉传感网络能够提供内容丰富的多角度视觉信息，在未来智能物联网中有着广泛的潜在应用。传统的"在网处理，分层传输"的信息获取框架制约着能量和带宽受限的无线视觉传感网络的实用性。本项目拟把分布式压缩感知应用到无线视觉传感网络中，研究多视点信息获取的新架构和新方法。研究内容包括：为避免在网节点管理和速率控制的交互开销，研究基于接收端压缩域流形学习的视点分簇和基于接收端虚拟队列的感知速率控制策略；通过对偶分解和反向背压机制实现多视点压缩感知信息的分布式跨层优化传输及其全局收敛性；通过多视点感知矩阵和冗余字典的联合设计以及基于相关几何变换的多视点联合重建降低感知速率要求，优化传输性能。本研究能够实现一种"分布式轻量在网压缩，协同优化传输，后端联合处理"的多视点信息获取新架构及一系列创新性的相关方法，从而提高无线视觉传感网络的有效运行时间，促进其在智能物联网中的应用，具有重要的科学意义和实用价值。

中文关键词： 压缩感知；虚拟队列；跨层优化；多视点；

英文摘要： Wireless Visual Sensor Networks (WVSN) can provide content-rich multi-view visual information and would have broad potential applications in the future intelligent Internet of Things (IOT). The traditional multi-view information acquisition architecture with in-network processing and layered transmission severely limits the practical application of energy- and bandwidth-limited WVSN. This project aims to develop a new architecture and related methods of multi-view information collection, transmission and reconstruction for WVSN based on the emerging Distributed Compressive Sensing (DCS) technique. The research content includes three aspects. To avoid communication overhead in in-network node management and rate control, visual nodes clustering based on compression-region manifold-learning in the receiver and measurement rate control based on the state of the visual queue of the receiver are firstly studied; optimal distributed cross-layer transmission and its global convergence are realized through dual decomposition and reverse back-pressure techniques; new methods for joint design of multi-view sensing matrix and redundant dictionary and joint reconstruction of compressive sensed multi-view information based geometric transformation are proposed to reduce sensing rate and farther optimize transmission performa

英文关键词： compressive sensing；virtual queue；cross-layer optimization；multi-view；