A depth camera based fall recognition system for the elderly

Rachit Dubey, Bingbing Ni, Pierre Moulin

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

Abstract

Falls are a great risk for elderly people living alone. Falls can result in serious injuries and in some cases even deaths. It is important to recognize them early and provide assistance. In this paper we present a novel computer vision based fall recognition system which combines depth map with normal color information. With this combination it is possible to achieve better results as depth map reduces many errors and gives more information about the scene. We track and extract motion from the depth as well RGB map and then use Support Vector Machines to classify the falls. Our proposed fall recognition system recognizes and classifies falls from other actions with a very high accuracy (greater than 95%).

Original languageEnglish (US)
Title of host publicationImage Analysis and Recognition - 9th International Conference, ICIAR 2012, Proceedings
Pages106-113
Number of pages8
EditionPART 2
DOIs
StatePublished - Jul 27 2012
Event9th International Conference on Image Analysis and Recognition, ICIAR 2012 - Aveiro, Portugal
Duration: Jun 25 2012Jun 27 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7325 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Image Analysis and Recognition, ICIAR 2012
CountryPortugal
CityAveiro
Period6/25/126/27/12

Keywords

  • SVM
  • depth image
  • fall detection
  • feature extraction

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'A depth camera based fall recognition system for the elderly'. Together they form a unique fingerprint.

Cite this