MINDEX: An efficient index structure for salient-object-based queries in video databases

Lei Chen, M. Tamer Özsu, Vincent Oria

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Several salient-object-based data models have been proposed to model video data. However, none of them addresses the development of an index structure to efficiently handle salient-object-based queries. There are several indexing schemes that have been proposed for spatiotemporal relationships among objects, and they are used to optimize times-tamp and internal queries, which are rarely used in video databases. Moreover, these index structures are designed without consideration of the granularity levels of constraints on salient objects and the characteristics of video data. In this paper, we propose a multilevel index structure (MINDEX) to efficiently handle the salient-object-based queries with different levels of constraints. We present experimental results showing the performance of different methods of MINDEX construction.

Original languageEnglish (US)
Pages (from-to)56-71
Number of pages16
JournalMultimedia Systems
Volume10
Issue number1
DOIs
StatePublished - Dec 1 2004

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications

Keywords

  • Content-based video retrieval
  • Multilevel indexes
  • Salient-object-based queries
  • Video data model

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