An efficient video indexing and retrieval algorithm using the luminance field trajectory modeling

Li Gao*, Zhu Li, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

With the phenomenal growth of the online and personal video repositories, an efficient and robust example-based video search solution is required to support applications like query by clip, query by capture, and repeated clip detection. In this letter, video sequences are represented as temporal trajectories via scaling and lower dimensional representation of the video frame luminance field, and a video trajectory indexing and matching scheme is developed to support video clip search. Simulation results demonstrate that the proposed approach achieves excellent performance in both response speed and precision-recall accuracy.

Original languageEnglish (US)
Article number5159407
Pages (from-to)1566-1570
Number of pages5
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume19
Issue number10
DOIs
StatePublished - Oct 1 2009

Keywords

  • Modeling
  • Subspace learning
  • Video indexing
  • Video retrieval

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'An efficient video indexing and retrieval algorithm using the luminance field trajectory modeling'. Together they form a unique fingerprint.

Cite this