A Skeleton Analysis Based Fall Detection Method Using ToF Camera

被引：5

作者：

Kong, Xiangbo ^{[1
]}

Kumaki, Takeshi ^{[1
]}

Meng, Lin ^{[1
]}

Tomiyama, Hiroyuki ^{[1
]}

机构：

[1] Ritsumeikan Univ, Coll Sci & Engn, 1-1-1 Noji Higashi, Kusatsu, Shiga 5258577, Japan

来源：

2020 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS (IIKI2020) | 2021年 / 187卷

关键词：

Skeleton; Fall Detection; ToF Camera; RADAR;

D O I：

10.1016/j.procs.2021.04.059

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Fall detection based on image processing is considered as a good solution. However, algorithms based on motion recognition are difficult to distinguish between a person who has fallen and a person who is sleeping. This research tracks and analyzes the motion speed of human joints, which improves the accuracy of fall detection. The experimental results prove that this method effectively distinguishes falling and sleeping. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the International Conference on Identification, Information and Knowledge in the internet of Things, 2020.

引用

页码：252 / 257

页数：6

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