METU-MMDS: An intelligent multimedia database system for multimodal content extraction and querying

Adnan Yazici, Saeid Sattari, Turgay Yilmaz, Mustafa Sert, Murat Koyuncu, Elvan Gulen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 22nd International Conference, MMM 2016, Proceedings
EditorsRichang Hong, Nicu Sebe, Qi Tian, Guo-Jun Qi, Benoit Huet, Xueliang Liu
PublisherSpringer Verlag
Pages354-360
Number of pages7
ISBN (Print)9783319276731
DOIs
Publication statusPublished - Jan 1 2016
Externally publishedYes
Event22nd International Conference on MultiMedia Modeling, MMM 2016 - Miami, United States
Duration: Jan 4 2016Jan 6 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9517
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on MultiMedia Modeling, MMM 2016
CountryUnited States
CityMiami
Period1/4/161/6/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'METU-MMDS: An intelligent multimedia database system for multimodal content extraction and querying'. Together they form a unique fingerprint.

  • Cite this

    Yazici, A., Sattari, S., Yilmaz, T., Sert, M., Koyuncu, M., & Gulen, E. (2016). METU-MMDS: An intelligent multimedia database system for multimodal content extraction and querying. In R. Hong, N. Sebe, Q. Tian, G-J. Qi, B. Huet, & X. Liu (Eds.), MultiMedia Modeling - 22nd International Conference, MMM 2016, Proceedings (pp. 354-360). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9517). Springer Verlag. https://doi.org/10.1007/978-3-319-27674-8_33