Detecting Fall Risk Factors for Toddlers

  • Authors:
  • Hana Na;Shengfeng Qin;David Wright

  • Affiliations:
  • LG Electronics;Brunel University;Brunel University

  • Venue:
  • IEEE Pervasive Computing
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Preventing accidental injuries of toddlers requires thorough, consistent supervision, but this isn't always practical. A proposed vision-based system detects three fall risk factors in the home environment to help caregivers supervise nearby toddlers when they can't give continuous attention to the toddlers. The crucial technical challenge is to differentiate a human from other foreground objects in the images. Unlike previous systems, this one uses multiple dynamic motion cues for human detection, employing cues related to human appearance.