Silhouette analysis for human action recognition based on supervised temporal t-SNE and incremental learning

IEEE Transactions on Image Processing

Volumn 24, Issue 10, 2015, Pages 3203-3217

  Cheng, Jian ^a   Liu, Haijun ^a   Wang, Feng ^a   Li, Hongsheng ^a   Zhu, Ce ^a  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Human action recognition; incremental learning; manifold learning; stochastic neighbor embedding

Indexed keywords

EMBEDDED SYSTEMS; MOTION ESTIMATION; STOCHASTIC SYSTEMS;

CLASS LABEL INFORMATIONS; HUMAN-ACTION RECOGNITION; INCREMENTAL LEARNING; LOCALITY PRESERVING PROJECTIONS; LOW DIMENSIONAL EMBEDDING; MANIFOLD LEARNING; STATE-OF-THE-ART METHODS; STOCHASTIC NEIGHBOR EMBEDDING;

GESTURE RECOGNITION;

ALGORITHM; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; MOTOR ACTIVITY; MOVEMENT (PHYSIOLOGY); PHOTOGRAPHY; PHYSIOLOGY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SUPERVISED MACHINE LEARNING; WHOLE BODY IMAGING;

ALGORITHMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MOTOR ACTIVITY; MOVEMENT; PATTERN RECOGNITION, AUTOMATED; PHOTOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; SUPERVISED MACHINE LEARNING; WHOLE BODY IMAGING;

EID: 84932605504     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2015.2441634     Document Type: Article

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