A hierarchical self-organizing approach for learning the patterns of motion trajectories

IEEE Transactions on Neural Networks

Volumn 15, Issue 1, 2004, Pages 135-144

  Hu, Weiming ^a   Xie, Dan ^a   Tan, Tieniu ^a  

^a INSTITUTE OF AUTOMATION   (China)

Author keywords

Anomaly detection; Behavior prediction; Hierarchical self organizing neural network; Trajectory analysis and learning

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; HIERARCHICAL SYSTEMS; IMAGE CODING; IMAGE SEGMENTATION; LEARNING SYSTEMS; NEURAL NETWORKS; PATTERN RECOGNITION; REAL TIME SYSTEMS; SYSTEMS ANALYSIS; VECTOR QUANTIZATION;

ANOMALY DETECTION; EVENT RECOGNITION; HIERARCHICAL SELF-ORGANIZING APPROACH; OBJECT BEHAVIOR PREDICTION; PATTERNS OF MOTION TRAJECTORIES; TRAJECTORY CODING;

MOTION ESTIMATION;

ARTICLE; ARTIFICIAL NEURAL NETWORK; LEARNING; MOTION;

LEARNING; MOTION; NEURAL NETWORKS (COMPUTER);

EID: 1242263786     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2003.820668     Document Type: Article

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