在卫星构型设计中,要进行视场遮挡分析来判断光学敏感器是否会因为受到卫星其它部件的遮挡而失效.为了取代以往低效的手工分析方法,设计了卫星光学敏感器视场遮挡分析工具.介绍了该工具的设计方法及功能.工具基于三维CAD软件SolidWorks...在卫星构型设计中,要进行视场遮挡分析来判断光学敏感器是否会因为受到卫星其它部件的遮挡而失效.为了取代以往低效的手工分析方法,设计了卫星光学敏感器视场遮挡分析工具.介绍了该工具的设计方法及功能.工具基于三维CAD软件SolidWorks,并以动态链接库(DLL,Dynamic Link Library)的形式与SolidWorks紧密集成.在设计中运用了计算机图形学原理,利用SolidWorks API函数和Visual Basic编程语言进行二次开发.工具能够在SolidWorks中对卫星装配体执行以下敏感器视场遮挡分析功能:定义敏感器视锥特性参数,绘制视场遮挡图和计算视场遮挡率.展开更多
Background modeling and subtraction is a fundamental problem in video analysis. Many algorithms have been developed to date, but there are still some challenges in complex environments, especially dynamic scenes in wh...Background modeling and subtraction is a fundamental problem in video analysis. Many algorithms have been developed to date, but there are still some challenges in complex environments, especially dynamic scenes in which backgrounds are themselves moving, such as rippling water and swaying trees. In this paper, a novel background modeling method is proposed for dynamic scenes by combining both tensor representation and swarm intelligence. We maintain several video patches, which are naturally represented as higher order tensors,to represent the patterns of background, and utilize tensor low-rank approximation to capture the dynamic nature. Furthermore, we introduce an ant colony algorithm to improve the performance. Experimental results show that the proposed method is robust and adaptive in dynamic environments, and moving objects can be perfectly separated from the complex dynamic background.展开更多
文摘在卫星构型设计中,要进行视场遮挡分析来判断光学敏感器是否会因为受到卫星其它部件的遮挡而失效.为了取代以往低效的手工分析方法,设计了卫星光学敏感器视场遮挡分析工具.介绍了该工具的设计方法及功能.工具基于三维CAD软件SolidWorks,并以动态链接库(DLL,Dynamic Link Library)的形式与SolidWorks紧密集成.在设计中运用了计算机图形学原理,利用SolidWorks API函数和Visual Basic编程语言进行二次开发.工具能够在SolidWorks中对卫星装配体执行以下敏感器视场遮挡分析功能:定义敏感器视锥特性参数,绘制视场遮挡图和计算视场遮挡率.
基金supported by National Natural Science Foundation of China (Grant Nos. 11301137 and 11371036)the National Science Foundation of Hebei Province of China (Grant No. A2014205100
文摘Background modeling and subtraction is a fundamental problem in video analysis. Many algorithms have been developed to date, but there are still some challenges in complex environments, especially dynamic scenes in which backgrounds are themselves moving, such as rippling water and swaying trees. In this paper, a novel background modeling method is proposed for dynamic scenes by combining both tensor representation and swarm intelligence. We maintain several video patches, which are naturally represented as higher order tensors,to represent the patterns of background, and utilize tensor low-rank approximation to capture the dynamic nature. Furthermore, we introduce an ant colony algorithm to improve the performance. Experimental results show that the proposed method is robust and adaptive in dynamic environments, and moving objects can be perfectly separated from the complex dynamic background.
