Ali, Mohammed A. and Hussain, Abir J. and Sadiq, Ahmed T. (2022) Human Body Posture Recognition Approaches. ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY, 10 (1). pp. 75-84. ISSN 2410-9355
Text (Research Article)
ARO.10930-VOL10.NO1.2022.ISSUE18-PP75-84.pdf - Published Version Available under License Creative Commons Attribution Non-commercial Share Alike. Download (858kB) |
Abstract
Human body posture recognition has become the focus of many researchers in recent years. Recognition of body posture is used in various applications, including surveillance, security, and health monitoring. However, these systems that determine the body’s posture through video clips, images, or data from sensors have many challenges when used in the real world. This paper provides an important review of how most essential hardware technologies are used in posture recognition systems. These systems capture and collect datasets through accelerometer sensors or computer vision. In addition, this paper presents a comparison study with state-of-the-art in terms of accuracy. We also present the advantages and limitations of each system and suggest promising future ideas that can increase the efficiency of the existing posture recognition system. Finally, the most common datasets applied in these systems are described in detail. It aims to be a resource to help choose one of the methods in recognizing the posture of the human body and the techniques that suit each method. It analyzes more than 80 papers between 2015 and 2020
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Acceleration based, Computer vision, Health monitoring, Human body posture recognition, Security |
Subjects: | Q Science > QM Human anatomy |
Divisions: | ARO-The Scientific Journal of Koya University > VOL 10, NO1 (2022) |
Depositing User: | Dr Salah Ismaeel Yahya |
Date Deposited: | 26 Sep 2022 07:21 |
Last Modified: | 26 Sep 2022 07:21 |
URI: | http://eprints.koyauniversity.org/id/eprint/324 |
Actions (login required)
View Item |