Name
Abstract | ||
|---|---|---|
State-of-the-art image retrieval techniques have been developed to support high-level (semantics) querying and browsing of images. For certain user queries, it is also very important to know about the information about the remote image databases on the Internet so that the queries can be guided toward the most relevant databases. In this paper, we introduce a novel system, Sem View, which supports both visual and semantic queries and intelligently ranks the distributed image databases for the queries. Our system summarizes the visual and semantic contents of each database in a metadatabase, which is a collection of automatically generated visual, semantic and statistical metadata. With the metadatabase, our system can effectively guide the user queries toward the most relevant image databases in a distributed environment for better retrieval performance. |
Year | Venue | Keywords |
|---|---|---|
2003 | DG.O | remote image databases,better retrieval performance,certain user query,semantic query,image databases,novel system,image retrieval system,relevant image databases,semantic content,relevant databases,state-of-the-art image retrieval technique,distributed environment,image retrieval |
Field | DocType | Citations |
Metadata,Automatic image annotation,Information retrieval,Metadatabase,Distributed Computing Environment,Computer science,Image retrieval,Semantics,The Internet,Visual Word | Conference | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Wang | 1 | 51 | 4.27 |
| Yimin Wu | 2 | 83 | 6.20 |
| Aidong Zhang | 3 | 2970 | 405.63 |