News video classification using multimodal classifiers and text-biased combination strategies

Peng Wang, Rui Cai, Shiqiang Yang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Automatic classification of video content is a key technique in video management. Such classification combines evidence from multiple modes, but most existing combination strategies use a unified approach to process multimodal features, neglecting the asymmetric impact of textual and audio-visual features. This paper presents a text-biased scheme integrating multiple modes in news video classifications. The combination strategy mainly depends on textual evidence with some input from audio-visual clues. The classification approach has been validated on large-scale live news videos.

Original languageEnglish
Pages (from-to)475-478
Number of pages4
JournalQinghua Daxue Xuebao/Journal of Tsinghua University
Volume45
Issue number4
StatePublished - Apr 2005
Externally publishedYes

Keywords

  • Feature fusion
  • Multimodal classifiers
  • Video classification

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