Weighted subspace filtering and ranking algorithms for video concept retrieval

Lin Lin, Chao Chen, Mei-Ling Shyu, Shu Ching Chen

Research output: Contribution to journal › Article

34 Citations (Scopus)

Abstract

The proposed framework, with weighted subspace filtering and ranking components, is the first attempt in multimedia research to apply multiple correspondence analysis to selected features while pruning data instances.

Original languageEnglish
Article number5765919
Pages (from-to)32-42
Number of pages11
JournalIEEE Multimedia
Volume18
Issue number3
DOIs
StatePublished - Jul 1 2011

Keywords

  • concept retrieval
  • dissimilarity measure
  • filtering
  • multiple correspondence analysis (MCA)
  • ranking

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Science Applications
  • Signal Processing
  • Media Technology

Cite this

Weighted subspace filtering and ranking algorithms for video concept retrieval. / Lin, Lin; Chen, Chao; Shyu, Mei-Ling; Chen, Shu Ching.

In: IEEE Multimedia, Vol. 18, No. 3, 5765919, 01.07.2011, p. 32-42.

Research output: Contribution to journal › Article

Lin, L, Chen, C, Shyu, M-L & Chen, SC 2011, 'Weighted subspace filtering and ranking algorithms for video concept retrieval', IEEE Multimedia, vol. 18, no. 3, 5765919, pp. 32-42. https://doi.org/10.1109/MMUL.2011.35
Lin L, Chen C, Shyu M-L, Chen SC. Weighted subspace filtering and ranking algorithms for video concept retrieval. IEEE Multimedia. 2011 Jul 1;18(3):32-42. 5765919. https://doi.org/10.1109/MMUL.2011.35
Lin, Lin ; Chen, Chao ; Shyu, Mei-Ling ; Chen, Shu Ching. / Weighted subspace filtering and ranking algorithms for video concept retrieval. In: IEEE Multimedia. 2011 ; Vol. 18, No. 3. pp. 32-42.
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