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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/101606

    Title: Vision-Based Fall Detection Through Shape Features
    Authors: 林智揚;LIN ,CHIH-YANG;*;Wang ,Shang-Ming;Hong ,Jia-Wei;Kang, Li-Wei;黃仲陵;Huang, Chung-Lin
    Contributors: 生物資訊與醫學工程學系
    Date: 2016-04
    Issue Date: 2016-11-08 10:15:58 (UTC+8)
    Abstract: 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.
    Relation: The Second IEEE International Conference on Multimedia Big Data
    Appears in Collections:[生物資訊與醫學工程學系 ] 期刊論文

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