In this paper,a modeling method for a pantograph-catenary system is put forward to investigate the dynamic contact behavior in space,taking into consideration of the appearance characteristics of the contact surfaces ...In this paper,a modeling method for a pantograph-catenary system is put forward to investigate the dynamic contact behavior in space,taking into consideration of the appearance characteristics of the contact surfaces of the pantograph and catenary.The dynamic performance of the pantograph-catenary system,including contact forces,accelerations,and the corresponding spectra,is analyzed.Furthermore,with the modeling method,the influences of contact wire irregularity and the vibration caused by the front pantograph on the rear pantograph for a pantograph-catenary system with double pantographs are investigated.The results show that the appearance characteristics of the contact surfaces play an important role in the dynamic contact behavior.The appearance characteristics should be considered to reasonably evaluate the dynamic performance of the pantograph-catenary system.展开更多
Nowadays,action recognition is widely applied in many fields.However,action is hard to define by single modality information.The difference between image recognition and action recognition is that action recognition n...Nowadays,action recognition is widely applied in many fields.However,action is hard to define by single modality information.The difference between image recognition and action recognition is that action recognition needs more modality information to depict one action,such as the appearance,the motion and the dynamic information.Due to the state of action evolves with the change of time,motion information must be considered when representing an action.Most of current methods define an action by spatial information and motion information.There are two key elements of current action recognition methods:spatial information achieved by sampling sparsely on video frames’sequence and the motion content mostly represented by the optical flow which is calculated on consecutive video frames.However,the relevance between them in current methods is weak.Therefore,to strengthen the associativity,this paper presents a new architecture consisted of three streams to obtain multi-modality information.The advantages of our network are:(a)We propose a new sampling approach to sample evenly on the video sequence for acquiring the appearance information;(b)We utilize ResNet101 for gaining high-level and distinguished features;(c)We advance a three-stream architecture to capture temporal,spatial and dynamic information.Experimental results on UCF101 dataset illustrate that our method outperforms other previous methods.展开更多
针对静态表情特征缺乏时间信息,不能充分体现表情的细微变化,该文提出一种针对非特定人的动态表情识别方法:基于动态时间规整(Dynamic Time Warping,DTW)和主动外观模型(Active Appearance Model,AAM)的动态表情识别。首先采用基于局部...针对静态表情特征缺乏时间信息,不能充分体现表情的细微变化,该文提出一种针对非特定人的动态表情识别方法:基于动态时间规整(Dynamic Time Warping,DTW)和主动外观模型(Active Appearance Model,AAM)的动态表情识别。首先采用基于局部梯度DT-CWT(Dual-Tree Complex Wavelet Transform)主方向模式(Dominant Direction Pattern,DDP)特征的DTW对表情序列进行规整。然后采用AAM定位出表情图像的66个特征点并进行跟踪,利用中性脸的特征点构建人脸几何模型,通过人脸几何模型的匹配克服不同人呈现表情的差异,并通过计算表情序列中相邻两帧图像对应特征点的位移获得表情的变化特征。最后采用最近邻分类器进行分类识别。在CK+库和实验室自建库HFUT-FE(He Fei University of Technology-Face Emotion)上的实验结果表明,所提算法具有较高的准确性。展开更多
基金Project supported by the National Natural Science Foundation of China (No.51075341)the National Basic Research Program (973) of China (No.2011CB711105)
文摘In this paper,a modeling method for a pantograph-catenary system is put forward to investigate the dynamic contact behavior in space,taking into consideration of the appearance characteristics of the contact surfaces of the pantograph and catenary.The dynamic performance of the pantograph-catenary system,including contact forces,accelerations,and the corresponding spectra,is analyzed.Furthermore,with the modeling method,the influences of contact wire irregularity and the vibration caused by the front pantograph on the rear pantograph for a pantograph-catenary system with double pantographs are investigated.The results show that the appearance characteristics of the contact surfaces play an important role in the dynamic contact behavior.The appearance characteristics should be considered to reasonably evaluate the dynamic performance of the pantograph-catenary system.
基金the National Natural Science Foundation of China(Nos.61672150,61907007)by the Fund of the Jilin Provincial Science and Technology Department Project(Nos.20180201089GX,20190201305JC)+1 种基金Provincial Department of Education Project(Nos.JJKH20190291KJ,JJKH20190294KJ,JJKH20190355KJ)the Fundamental Research Funds for the Central Universities(No.2412019FZ049).
文摘Nowadays,action recognition is widely applied in many fields.However,action is hard to define by single modality information.The difference between image recognition and action recognition is that action recognition needs more modality information to depict one action,such as the appearance,the motion and the dynamic information.Due to the state of action evolves with the change of time,motion information must be considered when representing an action.Most of current methods define an action by spatial information and motion information.There are two key elements of current action recognition methods:spatial information achieved by sampling sparsely on video frames’sequence and the motion content mostly represented by the optical flow which is calculated on consecutive video frames.However,the relevance between them in current methods is weak.Therefore,to strengthen the associativity,this paper presents a new architecture consisted of three streams to obtain multi-modality information.The advantages of our network are:(a)We propose a new sampling approach to sample evenly on the video sequence for acquiring the appearance information;(b)We utilize ResNet101 for gaining high-level and distinguished features;(c)We advance a three-stream architecture to capture temporal,spatial and dynamic information.Experimental results on UCF101 dataset illustrate that our method outperforms other previous methods.
文摘针对静态表情特征缺乏时间信息,不能充分体现表情的细微变化,该文提出一种针对非特定人的动态表情识别方法:基于动态时间规整(Dynamic Time Warping,DTW)和主动外观模型(Active Appearance Model,AAM)的动态表情识别。首先采用基于局部梯度DT-CWT(Dual-Tree Complex Wavelet Transform)主方向模式(Dominant Direction Pattern,DDP)特征的DTW对表情序列进行规整。然后采用AAM定位出表情图像的66个特征点并进行跟踪,利用中性脸的特征点构建人脸几何模型,通过人脸几何模型的匹配克服不同人呈现表情的差异,并通过计算表情序列中相邻两帧图像对应特征点的位移获得表情的变化特征。最后采用最近邻分类器进行分类识别。在CK+库和实验室自建库HFUT-FE(He Fei University of Technology-Face Emotion)上的实验结果表明,所提算法具有较高的准确性。
