Clustered blockwise PCA for representing visual data

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 27, Issue 10, 2005, Pages 1675-1679

  Nishino, Ko ^a   Nayar, Shree K ^a   Jebara, Tony ^a  

^a Columbia University ^*  (United States)

Author keywords

Clustering; Eigenvalues and eigenvectors; Natural image statistics; Principal component analysis; Region growing partitioning; Singular value decomposition

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTER VISION; EIGENVALUES AND EIGENFUNCTIONS; MATRIX ALGEBRA; PRINCIPAL COMPONENT ANALYSIS;

CLUSTERING; NATURAL IMAGE STATISTICS; SINGULAR VALUE DECOMPOSITION;

IMAGE PROCESSING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; PRINCIPAL COMPONENT ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS;

EID: 27644550273     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2005.193     Document Type: Article

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