论文标题
连续可变形对象的摄像机网络的覆盖范围优化
Coverage Optimization of Camera Network for Continuous Deformable Object
论文作者
论文摘要
在本文中，考虑到视觉覆盖的目的，考虑了一个可变形的对象。将对象轮廓离散地将其作为网格分配为采样点，并且变形表示为采样点的连续轨迹。为了降低计算复杂性，仔细选择了某些特征点，以表示连续变形过程，并且会传输可变形对象的视觉覆盖范围以覆盖特定特征点。特别是，可以选择对象轮廓上每个采样点的整个变形轨迹的矩形的顶点。然后提出了改进的狼包算法以解决优化问题。最后，给出模拟结果以证明摄像机网络所提出的部署方法的有效性。
In this paper, a deformable object is considered for cameras deployment with the aim of visual coverage. The object contour is discretized into sampled points as meshes, and the deformation is represented as continuous trajectories for the sampled points. To reduce the computational complexity, some feature points are carefully selected representing the continuous deformation process, and the visual coverage for the deformable object is transferred to cover the specific feature points. In particular, the vertexes of a rectangle that can contain the entire deformation trajectory of every sampled point on the object contour are chosen as the feature points. An improved wolf pack algorithm is then proposed to solve the optimization problem. Finally, simulation results are given to demonstrate the effectiveness of the proposed deployment method of camera network.
