Ali, MA, Hussain, AJ and Sadiq, AT (2022) Human Body Posture Recognition Approaches. ARO-The Scientific Journal of Koya University, 10 (1). pp. 75-84. ISSN 2410-9355

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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
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software Q Science > QM Human anatomy Q Science > QP Physiology
Divisions:	Computer Science & Mathematics
Publisher:	Koya University
SWORD Depositor:	A Symplectic
Date Deposited:	23 Nov 2022 14:00
Last Modified:	23 Nov 2022 14:00
DOI or ID number:	10.14500/aro.10930
URI:	https://researchonline.ljmu.ac.uk/id/eprint/18205

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