Error-Resistant Movement Detection Algorithm for the Elderly with Smart Mirroropen access
- Authors
- Yang, Bo-Seung; Kang, Tae-Won; Choi, Yong-Sik; Jung, Jin-Woo
- Issue Date
- Jul-2022
- Publisher
- MDPI
- Keywords
- slow-motion detection; pose estimation model; smart mirror; elder-friendly; artificial intelligence
- Citation
- Applied Sciences, v.12, no.14, pp 1 - 14
- Pages
- 14
- Indexed
- SCIE
SCOPUS
- Journal Title
- Applied Sciences
- Volume
- 12
- Number
- 14
- Start Page
- 1
- End Page
- 14
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/2929
- DOI
- 10.3390/app12147024
- ISSN
- 2076-3417
2076-3417
- Abstract
- As the elderly population increases globally, the demand for systems and algorithms that target the elderly is increasing. Focusing on the extendibility of smart mirrors, our purpose is to create a motion detection system based on video input by an attached device (an RGB camera). The motion detection system presented in this paper is based on an algorithm that returns a Boolean value indicating the detection of motion based on skeletal information. We analyzed the problems that occur when the adjacent frame subtraction method (AFSM) is used in the motion detection algorithm based on the skeleton-related output of the pose estimation model. We compared and tested the motion recognition rate for slow-motion with the previously used AFSM and the vector sum method (VSM) proposed in this paper. As an experimental result, the slow-motion detection rate showed an increase of 30-70%.
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- Appears in
Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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