An optimized low computational algorithm for human fall detection from depth images based on Support Vector Machine classification

Systems developed to classify human activities to identify unintentional falls are highly demanding and play an important role in our daily life. Human falls are the main obstacle for elderly people to live independently and it is also a major health concern due to aging population. Different approa...

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Vydané v:	2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) s. 407 - 412
Hlavní autori:	Mohd, Mohd Norzali Haji, Nizam, Y., Suhaila, S., Jamil, M. Mahadi Abdul
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.09.2017
Predmet:	Acceleration Accelerometers Assitive Technology Classification algorithms Daily Activities Depth Images Floors Head Human Posture Robot sensing systems Support vector machines SVM
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