Fall detection in dusky environment

Ying Nong Chen, Chi Hung Chuang, Hsin Min Lee, Chih Chang Yu, Kuo Chin Fan

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Accidental fall is the most prominent factor that causes the accidental death of elder people due to their slow body reaction. Automatic fall detection technology integrated in a health-care system can assist human monitoring the occurrence of fall, especially in dusky environments. In this paper, a novel fall detection system focusing mainly on dusky environments is proposed. In dusky environments, the silhouette images of human bodies extracted from conventional CCD cameras are usually imperfect due to the abrupt change of illumination. Thus, our work adopts a thermal imager to detect human bodies. The proposed approach adopts a coarse-to-fine strategy. Firstly, the downward optical flow features are extracted from the thermal images to identify fall-like actions in the coarse stage. The horizontal projection of motion history images (MHI) extracted from fall-like actions are then designed to verify the incident by the proposed nearest neighbor feature line embedding (NNFLE) in the fine stage. Experimental results demonstrate that the proposed method can distinguish the fall incidents with high accuracy even in dusky environments and overlapping situations.

Original languageEnglish
Article number16
JournalEurasip Journal on Image and Video Processing
Volume2016
Issue number1
DOIs
StatePublished - 1 Dec 2016

Keywords

  • Fall detection
  • Motion history image
  • Nearest neighbor feature line
  • Optical flow

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