Incremental multi-linear discriminant analysis using canonical correlations for action recognition

Neurocomputing

Volumn 83, Issue , 2012, Pages 56-63

  Jia, Cheng Cheng ^a   Wang, Su Jing ^a   Peng, Xu Jun ^b   Pang, Wei ^a,c   Zhang, Can Yan ^d   Zhou, Chun Guang ^a   Yu, Zhe Zhou ^a  

^a JILIN UNIVERSITY   (China)

^b BBN TECHNOLOGIES   (United States)

^c UNIVERSITY OF ABERDEEN   (United Kingdom)

^d HARBIN ENGINEERING UNIVERSITY   (China)

Author keywords

Action recognition; Canonical correlations analysis; Discriminant information; Incremental learning; Multi linear subspace

Indexed keywords

ACTION RECOGNITION; CANONICAL CORRELATIONS ANALYSIS; DISCRIMINANT INFORMATION; INCREMENTAL LEARNING; MULTI-LINEAR SUBSPACE;

DATA STRUCTURES; FEATURE EXTRACTION; TENSORS;

VECTORS;

ACCURACY; ARTICLE; CLASSIFICATION ALGORITHM; CLASSIFIER; COMPARATIVE EFFECTIVENESS; CONTROLLED STUDY; CORRELATION ANALYSIS; DISCRIMINANT ANALYSIS; INTERMETHOD COMPARISON; K NEAREST NEIGHBOR; LEARNING ALGORITHM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROBABILITY; PROCESS DEVELOPMENT; PROCESS OPTIMIZATION; SPATIAL FREQUENCY DISCRIMINATION; SYSTEMATIC ERROR; VISUAL MEMORY;

EID: 84856594128     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.11.006     Document Type: Article

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