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
A profound approach about dual arm robot collision free motion planning is made. The method of configuration space is first and successfully applied to the collision free motion planning of dual arm robot, and a n...A profound approach about dual arm robot collision free motion planning is made. The method of configuration space is first and successfully applied to the collision free motion planning of dual arm robot, and a new concept, slave arm collision state graph, is presented. In this algorithm ,the problem of dual arm robot collision free motion planning is reduced to a search in the collision state graph. With this algorithm, a time optimum trajectory would be found, or the condition that there is no feasible solution for the slave arm is proved. A verification of this algorithm is made in the dual arm horizontal articulated robot SCARATES, and the results ascertain that the algorithm is feasible and effective.展开更多
A graph theory model of the human nature structure( GMH) for machine vision and image/graphics processing is described in this paper. Independent from the motion and deformation of contours,the human nature structure(...A graph theory model of the human nature structure( GMH) for machine vision and image/graphics processing is described in this paper. Independent from the motion and deformation of contours,the human nature structure( HNS) embodies the most basic movement characteristics of the body. The human body can be divided into basic units like head,torso,and limbs. Using these basic units,a graph theory model for the HNS can be constructed. GMH provides a basic model for human posture processing,and the outline in the perspective projection plane is the body contour of an image. In addition,the GMH can be applied to articulated motion and deformable objects,e. g.,in the design and analysis of body posture,by modifying mapping parameters of the GMH.展开更多
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.
文摘A profound approach about dual arm robot collision free motion planning is made. The method of configuration space is first and successfully applied to the collision free motion planning of dual arm robot, and a new concept, slave arm collision state graph, is presented. In this algorithm ,the problem of dual arm robot collision free motion planning is reduced to a search in the collision state graph. With this algorithm, a time optimum trajectory would be found, or the condition that there is no feasible solution for the slave arm is proved. A verification of this algorithm is made in the dual arm horizontal articulated robot SCARATES, and the results ascertain that the algorithm is feasible and effective.
基金Supported by the National Natural Science Foundation of China(No.71373023,61372148,61571045)Beijing Advanced Innovation Center for Imaging Technology(No.BAICIT-2016002)+1 种基金the National Key Technology R&D Program(No.2014BAK08B02,2015BAH55F03)the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions(No.CIT&TCD201504039)
文摘A graph theory model of the human nature structure( GMH) for machine vision and image/graphics processing is described in this paper. Independent from the motion and deformation of contours,the human nature structure( HNS) embodies the most basic movement characteristics of the body. The human body can be divided into basic units like head,torso,and limbs. Using these basic units,a graph theory model for the HNS can be constructed. GMH provides a basic model for human posture processing,and the outline in the perspective projection plane is the body contour of an image. In addition,the GMH can be applied to articulated motion and deformable objects,e. g.,in the design and analysis of body posture,by modifying mapping parameters of the GMH.
