3D有向多媒体传感器网络视觉覆盖率优化

Visual Coverage Ratio Optimization in 3D Directional Multimedia Sensor Networks

3D多媒体传感器网络中的视觉信息的监测更为复杂多变,在感知模型设定、连通覆盖等方面均不同于2D,使得视觉覆盖面临许多新的问题.本文研究3D有向多媒体传感器网络视觉覆盖率优化机制.首先提出3D感知空间近似模型,对节点感知模型进行实例化,通过空间近似方法降低计算复杂度.在此基础上,设计空间冗余最小化的感知方向调整算法,提高节点视域利用率,进而优化视觉覆盖率和有向目标鉴别率.仿真实验结果表明,视觉覆盖率和目标鉴别率分别在随机分布的基础上提高了82.5%和27.6%,即利用该算法能够提高视觉覆盖率和目标鉴别率.

Monitoring visual information in 3D multimedia sensor networks is more complex than 2D in terms of perceptual model and connectivity coverage, leading to a number of new problems. The focus of this paper is on visual coverage ratio optimization in 3D directional multimedia sensor networks. We begin with a 3D perceptual space approximation model to simplify the node perceptual model and reduce computational complexity, followed by a design of perceptual direction adjustment algorithm, with an objective of improving the utilization of visual field and minimizing spatial redundancy. The simulation results demonstrate that visual coverage and target identification rates are increased 82.5% and 27.6% respectively on the basis of random distribution. The algorithm a- chieves oefformance imorovement in terms of visual coverage ratio and tareet recognition ratio.