The paper addresses the problem of target recognition using High-resolution Radar Range Profiles(HRRP).A novel approach of feature extraction and dimension reduction based on extended high order central moments is pro...The paper addresses the problem of target recognition using High-resolution Radar Range Profiles(HRRP).A novel approach of feature extraction and dimension reduction based on extended high order central moments is proposed in order to reduce the dimension of range profiles.Features extracted from radar HRRPs are normalized and smoothed,and then comparative analysis of the similar approaches is done.The range profiles are obtained by step frequency technique using the two-dimensional backscatters distribution data of four different aircraft models.The template matching method by nearest neighbor rules,which is based on the theory of kernel methods for pattern analysis,is used to classify and identify the range profiles from four different aircrafts.Numerical simulation results show that the proposed approach can achieve good performance of stability,shift independence and higher recognition rate.It is helpful for real-time identification and the engineering implements of automatic target recognition using HRRP.The number of required templates could be reduced con-siderably while maintaining an equivalent recognition rate.展开更多
To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic ...To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.展开更多
文摘The paper addresses the problem of target recognition using High-resolution Radar Range Profiles(HRRP).A novel approach of feature extraction and dimension reduction based on extended high order central moments is proposed in order to reduce the dimension of range profiles.Features extracted from radar HRRPs are normalized and smoothed,and then comparative analysis of the similar approaches is done.The range profiles are obtained by step frequency technique using the two-dimensional backscatters distribution data of four different aircraft models.The template matching method by nearest neighbor rules,which is based on the theory of kernel methods for pattern analysis,is used to classify and identify the range profiles from four different aircrafts.Numerical simulation results show that the proposed approach can achieve good performance of stability,shift independence and higher recognition rate.It is helpful for real-time identification and the engineering implements of automatic target recognition using HRRP.The number of required templates could be reduced con-siderably while maintaining an equivalent recognition rate.
基金Project(60801053) supported by the National Natural Science Foundation of ChinaProject(4082025) supported by the Beijing Natural Science Foundation,China+4 种基金Project(20070004037) supported by the Doctoral Foundation of ChinaProject(2009JBM135,2011JBM023) supported by the Fundamental Research Funds for the Central Universities of ChinaProject(151139522) supported by the Hongguoyuan Innovative Talent Program of Beijing Jiaotong University,ChinaProject(YB20081000401) supported by the Beijing Excellent Doctoral Thesis Program,ChinaProject (2006CB303105) supported by the National Basic Research Program of China
文摘To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.
