Collaborative Robotics is one of the high-interest research topics in the area of academia and industry.It has been progressively utilized in numerous applications,particularly in intelligent surveillance systems.It a...Collaborative Robotics is one of the high-interest research topics in the area of academia and industry.It has been progressively utilized in numerous applications,particularly in intelligent surveillance systems.It allows the deployment of smart cameras or optical sensors with computer vision techniques,which may serve in several object detection and tracking tasks.These tasks have been considered challenging and high-level perceptual problems,frequently dominated by relative information about the environment,where main concerns such as occlusion,illumination,background,object deformation,and object class variations are commonplace.In order to show the importance of top view surveillance,a collaborative robotics framework has been presented.It can assist in the detection and tracking of multiple objects in top view surveillance.The framework consists of a smart robotic camera embedded with the visual processing unit.The existing pre-trained deep learning models named SSD and YOLO has been adopted for object detection and localization.The detection models are further combined with different tracking algorithms,including GOTURN,MEDIANFLOW,TLD,KCF,MIL,and BOOSTING.These algorithms,along with detection models,help to track and predict the trajectories of detected objects.The pre-trained models are employed;therefore,the generalization performance is also investigated through testing the models on various sequences of top view data set.The detection models achieved maximum True Detection Rate 93%to 90%with a maximum 0.6%False Detection Rate.The tracking results of different algorithms are nearly identical,with tracking accuracy ranging from 90%to 94%.Furthermore,a discussion has been carried out on output results along with future guidelines.展开更多
We introduce a model to implement incremental update of views. The principle is that unless a view is accessed, the modification related to the view is not computed. This modification information is used only when vie...We introduce a model to implement incremental update of views. The principle is that unless a view is accessed, the modification related to the view is not computed. This modification information is used only when views are updated. Modification information is embodied in the classes (including inheritance classes and nesting classes) that derive the view. We establish a modify list consisted of tuples (one tuple for each view which is related to the class) to implement view update. A method is used to keep views from re-update. Key words object-oriented database - incremental computation - view-computation - engineering information system CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China(60235025)Biography: Guo Hai-ying (1971-), female, Ph. D, research direction: CAD and engineering information system.展开更多
Many definitions of pornography implicitly involve begging the question concerning its moral value. One exception to this is Michael Rea＇s 2001 definition. The present paper identifies some counter-intuitive conseque...Many definitions of pornography implicitly involve begging the question concerning its moral value. One exception to this is Michael Rea＇s 2001 definition. The present paper identifies some counter-intuitive consequences of this definition of pornography and seeks to amend it. The aim of the paper is to separate a definitional understanding of pornography from a normative understanding of pornography in order to lay the foundations for future, coherent moral thinking on the subject.展开更多
Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).Howe...Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).However,the sparse and disordered nature of the 3D point cloud poses significant challenges to feature extraction.Overcoming limitations is critical for 3D point cloud processing.3D point cloud object detection is a very challenging and crucial task,in which point cloud processing and feature extraction methods play a crucial role and have a significant impact on subsequent object detection performance.In this overview of outstanding work in object detection from the 3D point cloud,we specifically focus on summarizing methods employed in 3D point cloud processing.We introduce the way point clouds are processed in classical 3D object detection algorithms,and their improvements to solve the problems existing in point cloud processing.Different voxelization methods and point cloud sampling strategies will influence the extracted features,thereby impacting the final detection performance.展开更多
虚拟试验验证使能支撑框架(Virtual Test and evaluation enabling Architecture,VITA)是国内具有自主知识产权的虚拟试验核心框架,具有良好的互联互通互操作性能。为了统一描述和定义VITA对象模型,从而促进试验资源的重用和组合,提出一...虚拟试验验证使能支撑框架(Virtual Test and evaluation enabling Architecture,VITA)是国内具有自主知识产权的虚拟试验核心框架,具有良好的互联互通互操作性能。为了统一描述和定义VITA对象模型,从而促进试验资源的重用和组合,提出一种VITA定义语言,采用UML风格定义了VITA对象模型的元模型,并为语言规定了严格的语法定义。基于VITA定义语言,设计相应的编译器实现对语法的正确性、一致性检查,并自动编译生成VITA对象模型的框架代码,对应用开发人员屏蔽了大量结构复杂的底层接口代码开发工作,提高了应用的开发效率和可靠性,同时也降低了应用开发人员的门槛,为跨地域、跨平台、跨专业的大型虚拟试验应用搭建奠定基础。展开更多
基金the Framework of International Cooperation Program managed by the National Research Foundation of Korea(2019K1A3A1A8011295711).
文摘Collaborative Robotics is one of the high-interest research topics in the area of academia and industry.It has been progressively utilized in numerous applications,particularly in intelligent surveillance systems.It allows the deployment of smart cameras or optical sensors with computer vision techniques,which may serve in several object detection and tracking tasks.These tasks have been considered challenging and high-level perceptual problems,frequently dominated by relative information about the environment,where main concerns such as occlusion,illumination,background,object deformation,and object class variations are commonplace.In order to show the importance of top view surveillance,a collaborative robotics framework has been presented.It can assist in the detection and tracking of multiple objects in top view surveillance.The framework consists of a smart robotic camera embedded with the visual processing unit.The existing pre-trained deep learning models named SSD and YOLO has been adopted for object detection and localization.The detection models are further combined with different tracking algorithms,including GOTURN,MEDIANFLOW,TLD,KCF,MIL,and BOOSTING.These algorithms,along with detection models,help to track and predict the trajectories of detected objects.The pre-trained models are employed;therefore,the generalization performance is also investigated through testing the models on various sequences of top view data set.The detection models achieved maximum True Detection Rate 93%to 90%with a maximum 0.6%False Detection Rate.The tracking results of different algorithms are nearly identical,with tracking accuracy ranging from 90%to 94%.Furthermore,a discussion has been carried out on output results along with future guidelines.
文摘We introduce a model to implement incremental update of views. The principle is that unless a view is accessed, the modification related to the view is not computed. This modification information is used only when views are updated. Modification information is embodied in the classes (including inheritance classes and nesting classes) that derive the view. We establish a modify list consisted of tuples (one tuple for each view which is related to the class) to implement view update. A method is used to keep views from re-update. Key words object-oriented database - incremental computation - view-computation - engineering information system CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China(60235025)Biography: Guo Hai-ying (1971-), female, Ph. D, research direction: CAD and engineering information system.
文摘Many definitions of pornography implicitly involve begging the question concerning its moral value. One exception to this is Michael Rea＇s 2001 definition. The present paper identifies some counter-intuitive consequences of this definition of pornography and seeks to amend it. The aim of the paper is to separate a definitional understanding of pornography from a normative understanding of pornography in order to lay the foundations for future, coherent moral thinking on the subject.
文摘Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).However,the sparse and disordered nature of the 3D point cloud poses significant challenges to feature extraction.Overcoming limitations is critical for 3D point cloud processing.3D point cloud object detection is a very challenging and crucial task,in which point cloud processing and feature extraction methods play a crucial role and have a significant impact on subsequent object detection performance.In this overview of outstanding work in object detection from the 3D point cloud,we specifically focus on summarizing methods employed in 3D point cloud processing.We introduce the way point clouds are processed in classical 3D object detection algorithms,and their improvements to solve the problems existing in point cloud processing.Different voxelization methods and point cloud sampling strategies will influence the extracted features,thereby impacting the final detection performance.
文摘虚拟试验验证使能支撑框架(Virtual Test and evaluation enabling Architecture,VITA)是国内具有自主知识产权的虚拟试验核心框架,具有良好的互联互通互操作性能。为了统一描述和定义VITA对象模型,从而促进试验资源的重用和组合,提出一种VITA定义语言,采用UML风格定义了VITA对象模型的元模型,并为语言规定了严格的语法定义。基于VITA定义语言,设计相应的编译器实现对语法的正确性、一致性检查,并自动编译生成VITA对象模型的框架代码,对应用开发人员屏蔽了大量结构复杂的底层接口代码开发工作,提高了应用的开发效率和可靠性,同时也降低了应用开发人员的门槛,为跨地域、跨平台、跨专业的大型虚拟试验应用搭建奠定基础。
