Dictionary learning on multiple manifolds for image classification

Baodi Liu, Yuxiong Wang, Yujin Zhang

Research output: Contribution to journalArticlepeer-review


Traditional image classification algorithms based on sparse coding do not consider the relationships among different features. A dictionary learning algorithm was developed to overcome this shortcoming, in which the intrinsic geometrical structure of the multiple manifolds explicitly models the features embedded into a sparse coding algorithm. A coordinate descent algorithm was then used to solve the optimization problem. A convergence analysis was given that shows the algorithm will converge. Tests on three standard benchmark datasets show that the algorithm outperforms other state-of-the-art image classification algorithms.

Original languageEnglish (US)
Pages (from-to)575-579
Number of pages5
JournalQinghua Daxue Xuebao/Journal of Tsinghua University
Issue number4
StatePublished - Apr 2012
Externally publishedYes


  • Dictionary learning
  • Image classification
  • Multiple manifolds learning
  • Sparse coding

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Applied Mathematics


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