Video event detection is an important research area nowadays.Modeling the video event is a key problem in video event detection.In this paper,we combine dynamic description logic with linear time temporal logic to bui...Video event detection is an important research area nowadays.Modeling the video event is a key problem in video event detection.In this paper,we combine dynamic description logic with linear time temporal logic to build a logic system for video event detection.The proposed logic system is named as LTD_(ALCO)which can represent and inference the static,dynamic and temporal knowledge in one uniform logic system.Based on the LTD_(ALCO),a framework for video event detection is proposed.The video event detection framework can automatically obtain the logic description of video content with the help of ontology-based computer vision techniques and detect the specified video event based on satisfiability checking on LTD_(ALCO)formulas.展开更多
Fuzzy description logics are considered as the logical infrastructure of fuzzy knowledge representation on the semantic Web. To deal with fuzzy and dynamic knowledge on the semantic Web and its applications, a new fuz...Fuzzy description logics are considered as the logical infrastructure of fuzzy knowledge representation on the semantic Web. To deal with fuzzy and dynamic knowledge on the semantic Web and its applications, a new fuzzy extension of Attribute Language with Complement based on dynamic fuzzy logic called the dynamic fuzzy description logic （DFALC） is presented. The syntax and semantics of DFALC are formally defined, and the forms of axioms and assertions are specified. The DFALC provides more reasonable logic foundation for the semantic Web, and overcomes the insufficiency of using fuzzy description logic FALC to act as logical foundation for the semantic Web. The extended DFALC is more expressive than the existing fuzzy description logics and present more fuzzy information on the semantic Web.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.60933004,60903141,60903079,60775030 and 60775035)the National Basic Research Program of China(No.2007CB311004)+1 种基金National High Technology Research and Development Program of China(No.2007AA01Z132)the National Science and Technology Pillar Program(No.2006BAC08B06).
文摘Video event detection is an important research area nowadays.Modeling the video event is a key problem in video event detection.In this paper,we combine dynamic description logic with linear time temporal logic to build a logic system for video event detection.The proposed logic system is named as LTD_(ALCO)which can represent and inference the static,dynamic and temporal knowledge in one uniform logic system.Based on the LTD_(ALCO),a framework for video event detection is proposed.The video event detection framework can automatically obtain the logic description of video content with the help of ontology-based computer vision techniques and detect the specified video event based on satisfiability checking on LTD_(ALCO)formulas.
基金the National Natural Science Foundation of China (60673092)Key Project of Ministry of Education of China (205059)+2 种基金the 2006 Jiangsu Sixth Talented-Personnel Research Program (06-E-037)The Project of Jiangsu Key Laboratory of Computer Information Processing Technologythe Higher Education Graduate Research Innovation Program of Jiangsu Province
文摘Fuzzy description logics are considered as the logical infrastructure of fuzzy knowledge representation on the semantic Web. To deal with fuzzy and dynamic knowledge on the semantic Web and its applications, a new fuzzy extension of Attribute Language with Complement based on dynamic fuzzy logic called the dynamic fuzzy description logic （DFALC） is presented. The syntax and semantics of DFALC are formally defined, and the forms of axioms and assertions are specified. The DFALC provides more reasonable logic foundation for the semantic Web, and overcomes the insufficiency of using fuzzy description logic FALC to act as logical foundation for the semantic Web. The extended DFALC is more expressive than the existing fuzzy description logics and present more fuzzy information on the semantic Web.
