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
The Internet of Things (IoT) assumes that things interact and exchange information thus defining the future of pervasive computing environments. The integration between people and interconnected objects realizes a new...The Internet of Things (IoT) assumes that things interact and exchange information thus defining the future of pervasive computing environments. The integration between people and interconnected objects realizes a new physical and social space and opens new frontiers in context awareness and objects adaptation. In this paper we investigate the possibility of creating socially aware objects able to interact not only among themselves but also with human beings sharing the same environment. The main contribution of this work is to provide a knowledge model for social context-awareness and reasoning using an ontology-based context modeling, a user model and exploiting of social networks. This model is part of a larger framework called So Smart that aims at empowering networks of interconnected objects with social context awareness in order to improve their social interaction with people.展开更多
A context-aware privacy protection framework was designed for context-aware services and privacy control methods about access personal information in pervasive environment. In the process of user＇s privacy decision, ...A context-aware privacy protection framework was designed for context-aware services and privacy control methods about access personal information in pervasive environment. In the process of user＇s privacy decision, it can produce fuzzy privacy decision as the change of personal information sensitivity and personal information receiver trust. The uncertain privacy decision model was proposed about personal information disclosure based on the change of personal information receiver trust and personal information sensitivity. A fuzzy privacy decision information system was designed according to this model. Personal privacy control policies can be extracted from this information system by using rough set theory. It also solves the problem about learning privacy control policies of personal information disclosure.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.
文摘The Internet of Things (IoT) assumes that things interact and exchange information thus defining the future of pervasive computing environments. The integration between people and interconnected objects realizes a new physical and social space and opens new frontiers in context awareness and objects adaptation. In this paper we investigate the possibility of creating socially aware objects able to interact not only among themselves but also with human beings sharing the same environment. The main contribution of this work is to provide a knowledge model for social context-awareness and reasoning using an ontology-based context modeling, a user model and exploiting of social networks. This model is part of a larger framework called So Smart that aims at empowering networks of interconnected objects with social context awareness in order to improve their social interaction with people.
基金Supported by the National Natural Science Foundation of China (60573119, 604973098) and IBM joint project
文摘A context-aware privacy protection framework was designed for context-aware services and privacy control methods about access personal information in pervasive environment. In the process of user＇s privacy decision, it can produce fuzzy privacy decision as the change of personal information sensitivity and personal information receiver trust. The uncertain privacy decision model was proposed about personal information disclosure based on the change of personal information receiver trust and personal information sensitivity. A fuzzy privacy decision information system was designed according to this model. Personal privacy control policies can be extracted from this information system by using rough set theory. It also solves the problem about learning privacy control policies of personal information disclosure.
