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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 31, Number 8(3) (2019)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 2657-2668
S&M1963 Research Paper https://doi.org/10.18494/SAM.2019.2438 Published: August 30, 2019 Novel and Robust Vision- and System-on-chip-based Sensor for Fall Detection [PDF] Kuo-Liang Chung, Li-Ting Liu, and Chi-Huang Liao (Received May 20, 2019; Accepted July 22, 2019) Keywords: accuracy, fall detection, foreground construction, foreground detection, system on chip (SoC), vision computing
In this paper, we propose a novel and robust vision- and system-on-chip (SoC)-based system as a sensor to effectively detect falls of the elderly. The proposed method consists of five steps: initial light stability confirmation, gradient-difference-based foreground detection, dilationand multiframe-based foreground construction, false fall detection problem solving, and fall detection determination with a general-purpose input/output-based fall warning transmission. Real test videos have shown that our comprehensive experiments justify the low power, low hardware cost, and high detection accuracy merits of the proposed method when compared with related fall detection methods.
Corresponding author: Kuo-Liang Chung  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Kuo-Liang Chung, Li-Ting Liu, and Chi-Huang Liao, Novel and Robust Vision- and System-on-chip-based Sensor for Fall Detection, Sens. Mater., Vol. 31, No. 8, 2019, p. 2657-2668. |
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