Semisupervised feature selection via spline regression for video semantic recognition

IEEE Transactions on Neural Networks and Learning Systems

Volumn 26, Issue 2, 2015, Pages 252-264

  Han, Yahong ^a   Yang, Yi ^b   Yan, Yan ^b   Ma, Zhigang ^c   Sebe, Nicu ^d   Zhou, Xiaofang ^b,e  

^a TIANJIN UNIVERSITY   (China)

^b UNIVERSITY OF QUEENSLAND   (Australia)

^c Carnegie Mellon University   (United States)

^d UNIVERSITY OF TRENTO   (Italy)

^e SOOCHOW UNIVERSITY   (China)

Author keywords

semisupervised feature selection; spline regression; video analysis; 2,1

Indexed keywords

ALGORITHMS; ENCODING (SYMBOLS); GESTURE RECOGNITION; ITERATIVE METHODS; LINEAR TRANSFORMATIONS; MATRIX ALGEBRA; MOTION ESTIMATION; REGRESSION ANALYSIS; SEMANTICS; VIDEO RECORDING; VIDEO STREAMING;

FEATURE SELECTION ALGORITHM; HIGH DIMENSIONAL FEATURE; HUMAN-ACTION RECOGNITION; SEMI-SUPERVISED; STATE-OF-THE-ART METHODS; VIDEO ANALYSIS; VIDEO CONCEPT DETECTION; WITHIN-CLASS SCATTER MATRIX;

FEATURE EXTRACTION;

EID: 84921514115     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2014.2314123     Document Type: Article

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