A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divide the on-line graphics recognition process into four stages: preprocessing,shape classif...A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divide the on-line graphics recognition process into four stages: preprocessing,shape classification,shape fitting,and regularization. Attraction Force Model is employed to progressively combine the vertices on the input sketchy stroke and reduce the total number of vertices before the type of shape can be determined. After that ,the shape is fitted and gradually rectified to a regular one,thus the regularized shape fits the user intended one precisely.Experimental results show that this algorithm can yield good recognition precision(averagely above 90% )and fine regularization effect but with fast speed. Consequently,it is especially suitable to computational critical environment such as PDAs,which solely depends on a pen-based user interface.展开更多
针对传统上利用TCT(Transact Cost Theory)和RBV(Resource Based View)分析战略联盟成因的不足,试图利用ROT(Resource Operation Theory)建立联盟动态分析框架,认为权衡资源相对价值的过程贯穿于联盟形成与解体的始终,借助资源杠杆机制...针对传统上利用TCT(Transact Cost Theory)和RBV(Resource Based View)分析战略联盟成因的不足,试图利用ROT(Resource Operation Theory)建立联盟动态分析框架,认为权衡资源相对价值的过程贯穿于联盟形成与解体的始终,借助资源杠杆机制分析联盟运行全过程,主张当企业间达到杠杆决策均衡时,联盟形成,当杠杆失衡后,联盟解体。提出联盟存续期间的根本任务是针对外部资源的内化过程。最后借助企业在TBC(Time Based Competition)条件下的最优策略分析论证了本文结论。展开更多
文摘A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divide the on-line graphics recognition process into four stages: preprocessing,shape classification,shape fitting,and regularization. Attraction Force Model is employed to progressively combine the vertices on the input sketchy stroke and reduce the total number of vertices before the type of shape can be determined. After that ,the shape is fitted and gradually rectified to a regular one,thus the regularized shape fits the user intended one precisely.Experimental results show that this algorithm can yield good recognition precision(averagely above 90% )and fine regularization effect but with fast speed. Consequently,it is especially suitable to computational critical environment such as PDAs,which solely depends on a pen-based user interface.
文摘针对传统上利用TCT(Transact Cost Theory)和RBV(Resource Based View)分析战略联盟成因的不足,试图利用ROT(Resource Operation Theory)建立联盟动态分析框架,认为权衡资源相对价值的过程贯穿于联盟形成与解体的始终,借助资源杠杆机制分析联盟运行全过程,主张当企业间达到杠杆决策均衡时,联盟形成,当杠杆失衡后,联盟解体。提出联盟存续期间的根本任务是针对外部资源的内化过程。最后借助企业在TBC(Time Based Competition)条件下的最优策略分析论证了本文结论。
