{"title":"SEMCOG: a hybrid object-based image database system and its modeling, language, and query processing","authors":"Wen-Syan Li, K. Candan","doi":"10.1109/ICDE.1998.655788","DOIUrl":null,"url":null,"abstract":"Image data is structurally more complex than traditional types of data. An image can be viewed as a compound object containing many sub-objects. Each sub-object corresponds to image regions that are visually and semantically meaningful (e.g. car, man, etc.). We introduce a hierarchical structure for image modeling that supports image retrieval, at both the whole-image and object levels, using combinations of semantic expressions and visual examples. We introduce an image database system called SEMCOG (SEMantics and COGnition-based image retrieval). SEMCOG aims at integrating semantics- and cognition-based approaches and allows queries based on object-level information. We present a formal definition of a multimedia query language, we give details of the database's implementation and query processing, and we discuss our methods for merging similarities from different types of query criteria.","PeriodicalId":264926,"journal":{"name":"Proceedings 14th International Conference on Data Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1998-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 14th International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1998.655788","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Image data is structurally more complex than traditional types of data. An image can be viewed as a compound object containing many sub-objects. Each sub-object corresponds to image regions that are visually and semantically meaningful (e.g. car, man, etc.). We introduce a hierarchical structure for image modeling that supports image retrieval, at both the whole-image and object levels, using combinations of semantic expressions and visual examples. We introduce an image database system called SEMCOG (SEMantics and COGnition-based image retrieval). SEMCOG aims at integrating semantics- and cognition-based approaches and allows queries based on object-level information. We present a formal definition of a multimedia query language, we give details of the database's implementation and query processing, and we discuss our methods for merging similarities from different types of query criteria.