• DocumentCode
    1452136
  • Title

    Subspace Clustering

  • Author

    Vidal, René

  • Author_Institution
    He was coeditor of the book Dynamical Vision and has coauthored more than 100 articles in biomedical image analysis, computer vision, machine learning, hybrid systems, and robotics.
  • Volume
    28
  • Issue
    2
  • fYear
    2011
  • fDate
    3/1/2011 12:00:00 AM
  • Firstpage
    52
  • Lastpage
    68
  • Abstract
    Over the past few decades, significant progress has been made in clustering high-dimensional data sets distributed around a collection of linear and affine subspaces. This article presented a review of such progress, which included a number of existing subspace clustering algorithms together with an experimental evaluation on the motion segmentation and face clustering problems in computer vision.
  • Keywords
    computer vision; face recognition; image motion analysis; image segmentation; pattern clustering; affine subspace; computer vision; face clustering problem; high-dimensional data set clustering; linear subspace; motion segmentation; subspace clustering; Clustering algorithms; Data models; Noise; Polynomials; Principal component analysis; Signal processing algorithms; Subspace constraints;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2010.939739
  • Filename
    5714408
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1452136