Name
Title | ||
|---|---|---|
METU-MMDS: An Intelligent Multimedia Database System for Multimodal Content Extraction and Querying. |
Abstract | ||
|---|---|---|
Managing a large volume of multimedia data, which contain various modalities (visual, audio, and text), reveals the need for a specialized multimedia database system (MMDS) to efficiently model, process, store and retrieve video shots based on their semantic content. This demo introduces METU-MMDS, an intelligent MMDS which employs both machine learning and database techniques. The system extracts semantic content automatically by using visual, audio and textual data, stores the extracted content in an appropriate format and uses this content to efficiently retrieve video shots. The system architecture supports various multimedia query types including unimodal querying, multimodal querying, query-by-concept, query-by-example, and utilizes a multimedia index structure for efficiently querying multi-dimensional multimedia data. We demonstrate METU-MMDS for semantic data extraction from videos and complex multimedia querying by considering content and concept-based queries containing all modalities. |
Year | Venue | Field |
|---|---|---|
2016 | MMM | Modalities,Content extraction,Multimedia database,Information retrieval,Computer science,Systems architecture,Multimedia,Semantic data model |
DocType | Citations | PageRank |
Conference | 1 | 0.34 |
References | Authors | |
8 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adnan Yazici | 1 | 649 | 56.29 |
| Saeid Sattari | 2 | 7 | 1.43 |
| Turgay Yilmaz | 3 | 61 | 5.41 |
| Mustafa Sert | 4 | 36 | 12.37 |
| Murat Koyuncu | 5 | 89 | 10.32 |
| Elvan Gulen | 6 | 8 | 1.43 |