Fall detection based on body part tracking using a depth camera

IEEE Journal of Biomedical and Health Informatics

Volumn 19, Issue 2, 2015, Pages 430-439

  Bian, Zhen Peng ^a   Hou, Junhui ^a   Chau, Lap Pui ^a   Magnenat Thalmann, Nadia ^b  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

3 D; Computer vision; fall detection; head tracking; monocular; video surveillance

Indexed keywords

CAMERAS; COMPUTER VISION; DECISION TREES; IMAGE SEGMENTATION; SUPPORT VECTOR MACHINES; TREES (MATHEMATICS);

ELDERLY POPULATIONS; FALL DETECTION; HEAD TRACKING; MONOCULAR; RANDOMIZED DECISIONS; STATE-OF-THE-ART METHODS; SUPPORT VECTOR MACHINE CLASSIFIERS; VIDEO SURVEILLANCE;

SECURITY SYSTEMS;

ADULT; AMBULATORY MONITORING; DEVICES; FALLING; FEMALE; HEAD; HUMAN; IMAGE PROCESSING; MALE; PHYSIOLOGY; PROCEDURES; REPRODUCIBILITY; VIDEORECORDING; YOUNG ADULT;

ACCIDENTAL FALLS; ADULT; FEMALE; HEAD; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; MONITORING, AMBULATORY; REPRODUCIBILITY OF RESULTS; VIDEO RECORDING; YOUNG ADULT;

EID: 84924751134     PISSN: 21682194     EISSN: 21682208     Source Type: Journal    
DOI: 10.1109/JBHI.2014.2319372     Document Type: Article

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