Vision-based fall detection through shape features

Chih Yang Lin, Shang Ming Wang, Jia Wei Hong, Li Wei Kang, Chung Lin Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE 2nd International Conference on Multimedia Big Data, BigMM 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages237-240
Number of pages4
ISBN (Electronic)9781509021789
DOIs
Publication statusPublished - 2016 Aug 16
Externally publishedYes
Event2nd IEEE International Conference on Multimedia Big Data, BigMM 2016 - Taipei, Taiwan
Duration: 2016 Apr 202016 Apr 22

Publication series

NameProceedings - 2016 IEEE 2nd International Conference on Multimedia Big Data, BigMM 2016

Conference

Conference2nd IEEE International Conference on Multimedia Big Data, BigMM 2016
Country/TerritoryTaiwan
CityTaipei
Period2016/04/202016/04/22

Keywords

  • Fall detection
  • Motion features
  • Motion history image

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Media Technology

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