Sensor Placement Optimization Method for People Tracking
Sensor Placement Optimization Method for People Tracking
复制标题
用于人员跟踪的传感器放置优化方法
DOI：
10.1109/ngmast.2013.20
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Hirozumi Yamaguchi and Teruo Higashino
中科院分区：
文献类型：
--
作者：
Akihito Hiromori;Hirozumi Yamaguchi and Teruo Higashino
本文研究了多点行人流量监测系统中传感器位置优化问题，并给出了一种有效的算法。我们的目标是建立一个现实的和准确的监测系统的行人流量估计性能的估计误差方面的模型。此外，我们的模型可以代表传感器的位置，考虑在城市场景中的传感器的数量，类型，位置和能力。为了实现这一目标，我们制定了一个给定的监测系统在给定的传感器位置下实现的估计精度的子问题。使用求解器为这个子问题作为一个子模块，我们还设计了一个算法来确定最佳的传感器布局。该算法采用模拟退火（SA）的方法，并迭代地改善解决方案收敛到近最优解。通过使用我们的HumanS模拟器[1]进行性能评估，该模拟器完全模拟了人体检测传感器，行人行为和地板结构，我们已经验证了通过我们提出的方法导出的传感器放置可以高精度地检测地下城市的行人流量，其估计误差约为1%。
In this paper, we deal with a sensor placement optimization problem for multi-point pedestrian flow monitoring systems, and provide an efficient algorithm. Our goal is to build a realistic and accurate model of the monitoring systems' pedestrian flow estimation performance in terms of their estimation errors. Also our model can represent sensor placement considering the number, types, locations and capabilities of sensors in urban scenarios. To this goal, we formulate the sub-problem of estimating accuracy achieved by a given monitoring system under a given placement of sensors. Using a solver for this sub-problem as a sub-module, we also design an algorithm to determine the optimal sensor placement. This algorithm employs a simulated annealing (SA) based approach and iteratively improve solutions to converge to near optimal solutions. Through performance evaluation using our HumanS simulator [1], which simulates human detection sensors, pedestrian behavior and floor structures altogether, we have verified that a derived sensor placement by our proposed method could detect pedestrian flows with high accuracy for an underground city and its estimation error was about 1 percent.