Multimodal video database modeling, querying and browsing

Nurcan Durak, Adnan Yazici

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

1 Citation (Scopus)

Abstract

In this paper, a multimodal video indexing and retrieval system, MMVIRS, is presented. MMVIRS models the auditory, visual, and textual sources of video collections from a semantic perspective. Besides multimodality, our model is constituted on semantic hierarchies that enable us to access the video from different semantic levels. MMVIRS has been implemented with data annotation, querying and browsing parts. In the annotation part, metadata information and video semantics are extracted in hierarchical ways. In the querying part, semantic queries, spatial queries, regional queries, spatio-temporal queries, and temporal queries have been processed over video collections using the proposed model. In the browsing parts, video collections are navigated using category information, visual and auditory hierarchies.

Original languageEnglish
Title of host publicationComputer and Information Sciences - ISCIS 2005 - 20th International Symposium, Proceedings
Pages802-812
Number of pages11
DOIs
Publication statusPublished - 2005
Event20th International Symposium on Computer and Information Sciences, ISCIS 2005 - Istanbul, Turkey
Duration: Oct 26 2005Oct 28 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3733 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Symposium on Computer and Information Sciences, ISCIS 2005
Country/TerritoryTurkey
CityIstanbul
Period10/26/0510/28/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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