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JRM Vol.29 No.6 pp. 1057-1064
doi: 10.20965/jrm.2017.p1057
(2017)

Paper:

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

Lin Meng*, Xiangbo Kong*, and Daiki Taniguchi**

*College of Science and Engineering, Ritsumeikan University
1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan

**Grand Electronics, Inc.
754 Ayanishinotouin-cho, Shimogyou-ku, Kyoto-shi, Kyoto 600-8474, Japan

Received:
May 26, 2017
Accepted:
September 22, 2017
Published:
December 20, 2017
Keywords:
elderly persons protection, center of gravity, ellipse detection, dangerous situation detection
Abstract
Dangerous Situation Detection for Elderly Persons in Restrooms Using Center of Gravity and Ellipse Detection

Dangerous detection

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.

Cite this article as:
L. Meng, X. Kong, and D. Taniguchi, “Dangerous Situation Detection for Elderly Persons in Restrooms Using Center of Gravity and Ellipse Detection,” J. Robot. Mechatron., Vol.29, No.6, pp. 1057-1064, 2017.
Data files:
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Last updated on Aug. 14, 2018