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摘要翻译：
空中持续监视(PS)算法的开发、基准测试和验证需要获得专门的广域空中监视(WAAS)数据集。这种数据集很难获得，而且在空间分辨率和时间持续时间上往往都非常大。本文概述了一种模拟复杂城市环境的方法，并论证了利用这种方法生成模拟传感器数据的可行性，对应于使用广域成像系统进行监视和侦察应用。这为车辆跟踪算法和异常检测方法提供了一种经济有效的数据集生成方法。该系统将城市交通仿真(SUMO)交通仿真器与MATLAB控制器和图像生成器相融合，以创建包含在城市环境的大片区域中不间断的门到门旅行的场景。这种“生活模式”的方法提供了自然运动和交通流的三维视觉信息。然后，可以利用这一点来提供模拟传感器测量（例如，可视波段和红外视频图像）和自动获取地面真实数据，以评估多目标跟踪系统。
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英文标题：
《A System for the Generation of Synthetic Wide Area Aerial Surveillance
Imagery》
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作者：
Elias J Griffith, Chinmaya Mishra, Jason F. Ralph, Simon Maskell
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最新提交年份：
2018
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Other Computer Science 其他计算机科学
分类描述：This is the classification to use for documents that do not fit anywhere else.
这是用于不适合其他任何地方的文档的分类。
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一级分类：Computer Science 计算机科学
二级分类：Systems and Control 系统与控制
分类描述：cs.SY is an alias for eess.SY. This section includes theoretical and experimental research covering all facets of automatic control systems. The section is focused on methods of control system analysis and design using tools of modeling, simulation and optimization. Specific areas of research include nonlinear, distributed, adaptive, stochastic and robust control in addition to hybrid and discrete event systems. Application areas include automotive and aerospace control systems, network control, biological systems, multiagent and cooperative control, robotics, reinforcement learning, sensor networks, control of cyber-physical and energy-related systems, and control of computing systems.
cs.sy是eess.sy的别名。本部分包括理论和实验研究，涵盖了自动控制系统的各个方面。本节主要介绍利用建模、仿真和优化工具进行控制系统分析和设计的方法。具体研究领域包括非线性、分布式、自适应、随机和鲁棒控制，以及混合和离散事件系统。应用领域包括汽车和航空航天控制系统、网络控制、生物系统、多智能体和协作控制、机器人学、强化学习、传感器网络、信息物理和能源相关系统的控制以及计算系统的控制。
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一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Image and Video Processing 图像和视频处理
分类描述：Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.
用于图像、视频和多维信号的形成、捕获、处理、通信、分析和显示的理论、算法和体系结构。感兴趣的主题包括：数学，统计，和感知图像和视频建模和表示；线性和非线性滤波、去模糊、增强、恢复和重建退化、低分辨率或层析数据；无损和有损压缩编码；分割、对齐和识别；图像渲染、可视化和打印；计算成像，包括超声、断层和磁共振成像；以及图像和视频的分析、合成、存储、搜索和检索。
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英文摘要：
The development, benchmarking and validation of aerial Persistent Surveillance (PS) algorithms requires access to specialist Wide Area Aerial Surveillance (WAAS) datasets. Such datasets are difficult to obtain and are often extremely large both in spatial resolution and temporal duration. This paper outlines an approach to the simulation of complex urban environments and demonstrates the viability of using this approach for the generation of simulated sensor data, corresponding to the use of wide area imaging systems for surveillance and reconnaissance applications. This provides a cost-effective method to generate datasets for vehicle tracking algorithms and anomaly detection methods. The system fuses the Simulation of Urban Mobility (SUMO) traffic simulator with a MATLAB controller and an image generator to create scenes containing uninterrupted door-to-door journeys across large areas of the urban environment. This `pattern-of-life' approach provides three-dimensional visual information with natural movement and traffic flows. This can then be used to provide simulated sensor measurements (e.g. visual band and infrared video imagery) and automatic access to ground-truth data for the evaluation of multi-target tracking systems.
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PDF链接：
https://arxiv.org/pdf/1803.04856
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