This paper proposes a method to recognize human-object interactions by modeling context between human actions and interacted objects.Human-object interaction recognition is a challenging task due to severe occlusion b...This paper proposes a method to recognize human-object interactions by modeling context between human actions and interacted objects.Human-object interaction recognition is a challenging task due to severe occlusion between human and objects during the interacting process.Since that human actions and interacted objects provide strong context information,i.e.some actions are usually related to some specific objects,the accuracy of recognition is significantly improved for both of them.Through the proposed method,both global and local temporal features from skeleton sequences are extracted to model human actions.In the meantime,kernel features are utilized to describe interacted objects.Finally,all possible solutions from actions and objects are optimized by modeling the context between them.The results of experiments demonstrate the effectiveness of our method.展开更多
Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which ...Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which is crucial for intelligent applications,contradicts the lowdetection accuracy of human posture detection models in practical scenarios.To address this issue,a human pose estimation network called AT-HRNet has been proposed,which combines convolu-tional self-attention and cross-dimensional feature transformation.AT-HRNet captures significantfeature information from various regions in an adaptive manner,aggregating them through convolu-tional operations within the local receptive domain.The residual structures TripNeck and Trip-Block of the high-resolution network are designed to further refine the key point locations,wherethe attention weight is adjusted by a cross-dimensional interaction to obtain more features.To vali-date the effectiveness of this network,AT-HRNet was evaluated using the COCO2017 dataset.Theresults show that AT-HRNet outperforms HRNet by improving 3.2%in mAP,4.0%in AP75,and3.9%in AP^(M).This suggests that AT-HRNet can offer more beneficial solutions for human posture estimation.展开更多
为了满足固沙机功能集成化、智能化方向发展需求,设计了一种智能草沙障固沙机控制系统,采用主从式控制系统结构,以双Arduino Mega 2560为核心主控器,使用模块化对控制系统的硬件和软件进行设计;纵向铺设控制模块、底盘升降控制模块和播...为了满足固沙机功能集成化、智能化方向发展需求,设计了一种智能草沙障固沙机控制系统,采用主从式控制系统结构,以双Arduino Mega 2560为核心主控器,使用模块化对控制系统的硬件和软件进行设计;纵向铺设控制模块、底盘升降控制模块和播种控制模块采用增量式PID控制算法;横向铺设控制模块采用位置式PID控制算法,并结合YOLOv3实现草沙障的检测追踪;以触摸屏和基于蓝牙的固沙机控制Android APP为人机交互界面。控制系统试验结果表明:基于PID算法检测追踪方式与直插式铺设方式相比,采用检测追踪方式固沙机的横向犁沙宽度减小了78.7%,整车振动减小了42.6%,草沙障铺设和播种测试功能均达到样机设计预期,为智能化固沙机研究提供了一种切实可行的设计方案。展开更多
This paper discusses some issues on human reliability model of time dependent human behavior. Some results of the crew reliability experiment on Tsinghua training simulator in China are given, Meanwhile, a case of ca...This paper discusses some issues on human reliability model of time dependent human behavior. Some results of the crew reliability experiment on Tsinghua training simulator in China are given, Meanwhile, a case of calculation for human error probability during anticipated transient without scram (ATWS) based on the data drew from the recent experiment is offered.展开更多
文摘This paper proposes a method to recognize human-object interactions by modeling context between human actions and interacted objects.Human-object interaction recognition is a challenging task due to severe occlusion between human and objects during the interacting process.Since that human actions and interacted objects provide strong context information,i.e.some actions are usually related to some specific objects,the accuracy of recognition is significantly improved for both of them.Through the proposed method,both global and local temporal features from skeleton sequences are extracted to model human actions.In the meantime,kernel features are utilized to describe interacted objects.Finally,all possible solutions from actions and objects are optimized by modeling the context between them.The results of experiments demonstrate the effectiveness of our method.
基金the National Natural Science Foundation of China(No.61975015)the Research and Innovation Project for Graduate Students at Zhongyuan University of Technology(No.YKY2024ZK14).
文摘Human posture estimation is a prominent research topic in the fields of human-com-puter interaction,motion recognition,and other intelligent applications.However,achieving highaccuracy in key point localization,which is crucial for intelligent applications,contradicts the lowdetection accuracy of human posture detection models in practical scenarios.To address this issue,a human pose estimation network called AT-HRNet has been proposed,which combines convolu-tional self-attention and cross-dimensional feature transformation.AT-HRNet captures significantfeature information from various regions in an adaptive manner,aggregating them through convolu-tional operations within the local receptive domain.The residual structures TripNeck and Trip-Block of the high-resolution network are designed to further refine the key point locations,wherethe attention weight is adjusted by a cross-dimensional interaction to obtain more features.To vali-date the effectiveness of this network,AT-HRNet was evaluated using the COCO2017 dataset.Theresults show that AT-HRNet outperforms HRNet by improving 3.2%in mAP,4.0%in AP75,and3.9%in AP^(M).This suggests that AT-HRNet can offer more beneficial solutions for human posture estimation.
文摘为了满足固沙机功能集成化、智能化方向发展需求,设计了一种智能草沙障固沙机控制系统,采用主从式控制系统结构,以双Arduino Mega 2560为核心主控器,使用模块化对控制系统的硬件和软件进行设计;纵向铺设控制模块、底盘升降控制模块和播种控制模块采用增量式PID控制算法;横向铺设控制模块采用位置式PID控制算法,并结合YOLOv3实现草沙障的检测追踪;以触摸屏和基于蓝牙的固沙机控制Android APP为人机交互界面。控制系统试验结果表明:基于PID算法检测追踪方式与直插式铺设方式相比,采用检测追踪方式固沙机的横向犁沙宽度减小了78.7%,整车振动减小了42.6%,草沙障铺设和播种测试功能均达到样机设计预期,为智能化固沙机研究提供了一种切实可行的设计方案。
文摘This paper discusses some issues on human reliability model of time dependent human behavior. Some results of the crew reliability experiment on Tsinghua training simulator in China are given, Meanwhile, a case of calculation for human error probability during anticipated transient without scram (ATWS) based on the data drew from the recent experiment is offered.
