Depth-based human fall detection via shape features and improved extreme learning machine

IEEE Journal of Biomedical and Health Informatics

Volumn 18, Issue 6, 2014, Pages 1915-1922

  Ma, Xin ^a   Wang, Haibo ^a   Xue, Bingxia ^a   Zhou, Mingang ^a   Ji, Bing ^a   Li, Yibin ^a  

^a SHANDONG UNIVERSITY   (China)

Author keywords

Curvature scale space (CSS); extreme learning machine (ELM); fall detection; particle swarm optimization; shape contour

Indexed keywords

COSTS; CURVE FITTING; KNOWLEDGE ACQUISITION; PARTICLE SWARM OPTIMIZATION (PSO); VIDEO CAMERAS;

COMPUTER VISION TECHNIQUES; CURVATURE SCALE SPACES; EXTREME LEARNING MACHINE; FALL DETECTION; HUMAN FALL DETECTION; NUMBER OF HIDDEN NEURONS; PARTICLE SWARM OPTIMIZATION ALGORITHM; SHAPE CONTOURS;

LEARNING SYSTEMS;

ALGORITHM; AMBULATORY MONITORING; ARTIFICIAL INTELLIGENCE; BODY POSTURE; FALLING; FEMALE; HUMAN; IMAGE PROCESSING; MALE; PHYSIOLOGY; PROCEDURES; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; WALKING;

ACCIDENTAL FALLS; ALGORITHMS; ARTIFICIAL INTELLIGENCE; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; MODELS, STATISTICAL; MONITORING, AMBULATORY; POSTURE; SENSITIVITY AND SPECIFICITY; WALKING;

EID: 84904492894     PISSN: 21682194     EISSN: 21682208     Source Type: Journal    
DOI: 10.1109/JBHI.2014.2304357     Document Type: Article

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