@inproceedings{fc1199c73c914461bc4efa3a9a2e5f74,
title = "Vision-based fall detection through shape features",
abstract = "A major cause of deaths among the elderly relates to accidental falls. Such falls are of particular medical concern to this population because they often result in severe injuries, since senior citizens usually live alone and cannot ask for help when accidents happen. In this paper, we propose a fall detection system with the help of a Gaussian mixture background model to build the background before motion history image (MHI) is applied to analyze the fall behavior. Finally, two extra features, acceleration and angular acceleration, are proposed to more accurately determine whether a fall event has happened.",
keywords = "Fall detection, Motion features, Motion history image",
author = "Lin, {Chih Yang} and Wang, {Shang Ming} and Hong, {Jia Wei} and Kang, {Li Wei} and Huang, {Chung Lin}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2nd IEEE International Conference on Multimedia Big Data, BigMM 2016 ; Conference date: 20-04-2016 Through 22-04-2016",
year = "2016",
month = aug,
day = "16",
doi = "10.1109/BigMM.2016.22",
language = "???core.languages.en_GB???",
series = "Proceedings - 2016 IEEE 2nd International Conference on Multimedia Big Data, BigMM 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "237--240",
booktitle = "Proceedings - 2016 IEEE 2nd International Conference on Multimedia Big Data, BigMM 2016",
}