ROCAS: A Robust Online Algorithm for Spatial Partitioning in Distributed Smart Camera Systems
ROCAS: A Robust Online Algorithm for Spatial Partitioning in Distributed Smart Camera Systems
复制标题
ROCAS：分布式智能相机系统中空间分区的鲁棒在线算法
DOI：
10.1109/icdsc.2007.4357533
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
J. Hähner
中科院分区：
文献类型：
--
作者：
Martin Hoffmann;J. Hähner
基于视觉的监视系统例如用于观察大区域以检测入侵者并保护安全关键设备。这些大片区域可能是海港或机场停机坪，由于成本问题，通常无法仅由人力人员进行保护。如今用于观察这些区域的大多数监视系统都依赖于集中式系统架构，其中中央实体是系统的单点故障。在本文中，提出了一种自优化的系统架构的网络供应链。这意味着SC能够自主决定如何安排其视野，以实现最佳的空间监视覆盖。此外，分布式算法允许在线空间分区和检测失败的节点进行描述和评估。评估结果表明，接近最佳的空间分区，可以实现没有任何节点的所有摄像机在系统中的知识。
Vision based surveillance systems are used for example for the observation of large areas to detect intruders and protect safety critical equipment. These large areas may be maritime ports or aprons of airports and can usually not be guarded solely by human staff due to the costs arising. Most of today's surveillance systems used for the observation of these areas rely on a centralised system architecture with a central entity being the system's single point of failure. In this paper, a self-optimising system architecture for networked SCs is proposed. This implies SCs being able to decide autonomously how to arrange their fields of view to achieve an optimal spatial surveillance coverage. Additionally, a distributed algorithm allowing for online spatial partitioning and detection of failing nodes is described and evaluated. The evaluation shows that near optimal spatial partitioning can be achieved without any node having knowledge of all cameras in the system.