Constrained nonnegative matrix factorization for image representation

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 34, Issue 7, 2012, Pages 1299-1311

  Liu, Haifeng ^a   Wu, Zhaohui ^a   Li, Xuelong ^b   Cai, Deng ^c   Huang, Thomas S ^d  

^a ZHEJIANG UNIVERSITY   (China)

^b XI AN INSTITUTE OF OPTICS AND PRECISION MECHANICS   (China)

^c ZHEJIANG UNIVERSITY   (China)

^d University of Illinois at Urbana Champaign   (United States)

Author keywords

clustering; dimension reduction; Nonnegative matrix factorization; semi supervised learning

Indexed keywords

CLUSTERING; DIMENSION REDUCTION; DISCRIMINATING POWER; EMPIRICAL EXPERIMENTS; IMAGE REPRESENTATIONS; LABEL INFORMATION; LINEAR REPRESENTATION; MATRIX DECOMPOSITION; NONNEGATIVE MATRIX FACTORIZATION; NOVEL ALGORITHM; OPTIMIZATION PROBLEMS; REAL-WORLD APPLICATION; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING; STATE-OF-THE-ART APPROACH; UNSUPERVISED METHOD;

ALGORITHMS; SUPERVISED LEARNING;

COMPUTER VISION;

EID: 84861310732     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2011.217     Document Type: Article

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