Dangerous Situation Detection for Elderly Persons in Restrooms Using Center of Gravity and Ellipse Detection

Author:

Meng Lin,Kong Xiangbo,Taniguchi Daiki, ,

Abstract

We developed a restroom danger detection system (RDDS) for detecting dangerous situations and protecting the elderly. Restrooms are particularly dangerous places for elderly persons. Our RDDS detects danger in real time by using image processing and sends an alert to a family member, hospital staff, etc. It comprises four processes: person detection, center of gravity detection, ellipse detection, and danger decision. The human detection process calculates the difference between an image of the empty restroom and one of the restroom when it is occupied (to which a brightness correction has been applied). The difference image is binarized and used for detecting the presence of a person. If a person is detected, the person’s center of gravity and ellipse are detected in the binarized image after it is denoised. The obtained information is used for detecting a dangerous situation. If the dangerous situation continues for 60 seconds, an alert is sent. Testing showed that our system can detect a dangerous situation within 1.5 seconds. This RDDS is one step toward the development of a comprehensive elderly person protection system.

Publisher

Fuji Technology Press Ltd.

Subject

Electrical and Electronic Engineering,General Computer Science

Reference17 articles.

1. N. Noury, A. Fleury, P. Rumeau, A. K. Bourke, G. O. Laighin, V. Rialle, and J. E. Lundy, “Fall detection – principles and methods,” 29th Annual Int. Conf. of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), pp. 1663-1666, 2007.

2. N. Noury, P. Rumeau, A. K. Bourke, G. O. Laighin, and J. E. Lundy, “A proposal for the classification and evaluation of fall detectors,” IRBM, Vol.29, No.6, pp. 340-349, 2008.

3. J. Tao, M. Turjo, M. F. Wong, M. Wang, and Y. P. Tan, “Fall incidents detection for intelligent video surveillance,” Fifth Int. Conf. on Information, Communications and Signal Processing, pp. 1590-1594, 2005.

4. B. Toreyin, Y. Dedeoglu, and A. Cetin, “Hmm based falling person detection using both audio and video,” Proc. IEEE Int. Workshop on Human-Computer Interaction, pp. 211-220, 2005.

5. D. Anderson, J. M. Keller, M. Skubic, X. Chen, and Z. He, “Recognizing falls from silhouettes,” Int. Conf. of the IEEE Engineering in Medicine and Biology Society, pp. 6388-6391, 2006.

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3