{"title":"视频语义标注框架","authors":"P. Natarajan, R. Nevatia","doi":"10.1109/ICCV.2005.255","DOIUrl":null,"url":null,"abstract":"Semantic annotation of multimedia data is needed for various tasks like content based indexing of databases and also for making inferences about the activities taking place in the environment. In this paper, we present a top level ontology which provides a framework for describing the semantic features in video. We do this in three steps - First, we identify the key components of semantic descriptions like objects and events and how domain specific ontologies can be developed from them. Second, we present a set of predicates for composing events and for describing various spatio-temporal relationships between events/entities. Third, we develop a scheme for reasoning with the developed ontologies to infer complex events from simple events using relational algebra. Finally, we have demonstrated the utility of our framework by developing an ontology for a specific domain. We conclude by analyzing the performance of the reasoning mechanism with simulated events in this domain.","PeriodicalId":432729,"journal":{"name":"Tenth IEEE International Conference on Computer Vision Workshops (ICCVW'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"EDF: A framework for Semantic Annotation of Video\",\"authors\":\"P. Natarajan, R. Nevatia\",\"doi\":\"10.1109/ICCV.2005.255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Semantic annotation of multimedia data is needed for various tasks like content based indexing of databases and also for making inferences about the activities taking place in the environment. In this paper, we present a top level ontology which provides a framework for describing the semantic features in video. We do this in three steps - First, we identify the key components of semantic descriptions like objects and events and how domain specific ontologies can be developed from them. Second, we present a set of predicates for composing events and for describing various spatio-temporal relationships between events/entities. Third, we develop a scheme for reasoning with the developed ontologies to infer complex events from simple events using relational algebra. Finally, we have demonstrated the utility of our framework by developing an ontology for a specific domain. We conclude by analyzing the performance of the reasoning mechanism with simulated events in this domain.\",\"PeriodicalId\":432729,\"journal\":{\"name\":\"Tenth IEEE International Conference on Computer Vision Workshops (ICCVW'05)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tenth IEEE International Conference on Computer Vision Workshops (ICCVW'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCV.2005.255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tenth IEEE International Conference on Computer Vision Workshops (ICCVW'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2005.255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Semantic annotation of multimedia data is needed for various tasks like content based indexing of databases and also for making inferences about the activities taking place in the environment. In this paper, we present a top level ontology which provides a framework for describing the semantic features in video. We do this in three steps - First, we identify the key components of semantic descriptions like objects and events and how domain specific ontologies can be developed from them. Second, we present a set of predicates for composing events and for describing various spatio-temporal relationships between events/entities. Third, we develop a scheme for reasoning with the developed ontologies to infer complex events from simple events using relational algebra. Finally, we have demonstrated the utility of our framework by developing an ontology for a specific domain. We conclude by analyzing the performance of the reasoning mechanism with simulated events in this domain.