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Proceedings Paper

A vision-based fall detection algorithm of human in indoor environment
Author(s): Hao Liu; Yongcai Guo
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Paper Abstract

Elderly care becomes more and more prominent in China as the population is aging fast and the number of aging population is large. Falls, as one of the biggest challenges in elderly guardianship system, have a serious impact on both physical health and mental health of the aged. Based on feature descriptors, such as aspect ratio of human silhouette, velocity of mass center, moving distance of head and angle of the ultimate posture, a novel vision-based fall detection method was proposed in this paper. A fast median method of background modeling with three frames was also suggested. Compared with the conventional bounding box and ellipse method, the novel fall detection technique is not only applicable for recognizing the fall behaviors end of lying down but also suitable for detecting the fall behaviors end of kneeling down and sitting down. In addition, numerous experiment results showed that the method had a good performance in recognition accuracy on the premise of not adding the cost of time.

Paper Details

Date Published: 28 February 2017
PDF: 6 pages
Proc. SPIE 10256, Second International Conference on Photonics and Optical Engineering, 1025644 (28 February 2017); doi: 10.1117/12.2257902
Show Author Affiliations
Hao Liu, Chongqing Univ. (China)
Yongcai Guo, Chongqing Univ. (China)

Published in SPIE Proceedings Vol. 10256:
Second International Conference on Photonics and Optical Engineering
Chunmin Zhang; Anand Asundi, Editor(s)

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