Human gait recognition via deterministic learning

Neural Networks

Volumn 35, Issue , 2012, Pages 92-102

  Zeng, Wei ^a,b   Wang, Cong ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b LONGYAN UNIVERSITY   (China)

Author keywords

Deterministic learning; Dynamical pattern recognition; Feature extraction; Human gait recognition; RBF neural network; Side silhouette lower limb joint angle and angular velocity

Indexed keywords

DETERMINISTIC LEARNING; DYNAMICAL PATTERN; FEATURE DIMENSIONS; GAIT FEATURES; GAIT PATTERN; HUMAN BODIES; HUMAN GAIT; JOINT ANGLE; LOWER LIMB; MODEL BASED APPROACH; PHASE PORTRAIT; QUASI-PERIODIC; RADIAL BASIS FUNCTION NEURAL NETWORKS; RBF NEURAL NETWORK; RECOGNITION ERROR; SIGNATURE DATA; SIMILARITY MEASURE; SYSTEM DYNAMICS; TIME INVARIANTS; TIME VARYING; TRAINING PHASE; VELOCITY STATE;

ANGULAR VELOCITY; FEATURE EXTRACTION; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; SYSTEM THEORY; TESTING;

GAIT ANALYSIS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; GAIT; HUMAN; HUMAN EXPERIMENT; LEARNING; LOCOMOTION; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; PATTERN RECOGNITION; PRIORITY JOURNAL; TRAINING; VELOCITY; WALKING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; GAIT; HUMANS; JOINTS; LOCOMOTION; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 84865998843     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2012.07.012     Document Type: Article

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