English  |  正體中文  |  简体中文  |  Items with full text/Total items : 90429/105609 (86%)
Visitors : 10444785      Online Users : 677
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    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

    Files in This Item:

    File SizeFormat
    index.html0KbHTML95View/Open


    All items in ASIAIR are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback