High-order local spatial context modeling by spatialized random forest

IEEE Transactions on Image Processing

Volumn 22, Issue 2, 2013, Pages 739-751

  Ni, Bingbing ^a   Yan, Shuicheng ^b   Wang, Meng ^c   Kassim, Ashraf A ^b   Tian, Qi ^d  

^a ADVANCED DIGITAL SCIENCES CENTER   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c HEFEI UNIVERSITY OF TECHNOLOGY   (China)

^d One UTSA Circle   (United States)

Author keywords

Object classification; random forest; spatial context; visual codebook

Indexed keywords

CAPABILITY TEST; CO-OCCURRENCE; CODEBOOKS; DISCRIMINATING POWER; HIGH-ORDER; NEIGHBOR SELECTION; OBJECT CLASSIFICATION; RANDOM FORESTS; RANDOM PARTITIONS; SECOND ORDERS; SPATIAL CONTEXT; SPATIAL PATTERNS; STATE-OF-THE-ART APPROACH; TREE CONSTRUCTION; TREE NODES;

CLASSIFICATION (OF INFORMATION); FACE RECOGNITION; FORESTRY;

DECISION TREES;

CLASSIFICATION; DECISION MAKING; FORESTRY; INFORMATION RETRIEVAL; TREES;

ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOMETRY; DECISION TREE; FACE; FACTUAL DATABASE; HISTOLOGY; HUMAN; IMAGE PROCESSING; METHODOLOGY; REPRODUCIBILITY;

ARTIFICIAL INTELLIGENCE; BIOMETRIC IDENTIFICATION; DATABASES, FACTUAL; DECISION TREES; FACE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS;

MLCS; MLOWN;

EID: 84872360046     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2012.2222895     Document Type: Article

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