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Advancements in Human Activity Recognition: A Comprehensive Survey of Sensor-Based and Vision-Based Approaches

    Authors

    • kawther dhiya yassen 1
    • Hawraa H. Abass 2
    • Arwa Hameed 3

    1 Department of Electrical and Electronic Engineering, University of Kerbala, Kerbala, Iraq

    2 College of Information Technology Engineering, Al-Zahraa University for Women 56001 Karbala, Iraq

    3 Department of Electrical and Electronics Engineering, University of Kerbala, Kerbala, Iraq

,

Document Type : Review Article

10.63463/kjes1137
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Abstract

The significance of human activity recognition (HAR) has increased in recent years because of its wide-ranging applications in areas such as healthcare, security and surveillance, entertainment, and intelligent settings. A significant challenge in computer vision is the automated and accurate recognition of human actions. This survey presents the last related work conducted over the 2015–2023 years in various areas of human activity recognition. It introduces the classification of HAR basic methodologies. In general, HAR approaches are categorized into two primary groups: sensor-based and vision-based HAR. This classification is based on the type of created data and the system environment itself. Based on our study, smart phones, smart watches, accelerometers, gyroscopes, and arm bands are all examples of sensor-based techniques. For the vision-based techniques, there are cameras, Microsoft Kinect, and thermal cameras. Also categorized the general datasets referenced in academic papers are based on the type of activity: individual actions, behaviors, interactions, and group activities. Subsequently, the preprocessing and feature engineering procedures are demonstrated. At long last, this review is able to offer some study concepts that investigate and analyze HAR.

Keywords

  • Human activity recognition (HAR)
  • Vision-based
  • sensor-based
  • popular dataset
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Kerbala Journal for Engineering Sciences
Volume 4, Issue 3
September 2024
Pages 203-234
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How to cite
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  • Article View: 2,989
  • PDF Download: 131

APA

yassen, K., Abass, H., & Hameed, A. (2024). Advancements in Human Activity Recognition: A Comprehensive Survey of Sensor-Based and Vision-Based Approaches. Kerbala Journal for Engineering Sciences, 4(3), 203-234. doi: 10.63463/kjes1137

MLA

kawther dhiya yassen; Hawraa H. Abass; Arwa Hameed. "Advancements in Human Activity Recognition: A Comprehensive Survey of Sensor-Based and Vision-Based Approaches". Kerbala Journal for Engineering Sciences, 4, 3, 2024, 203-234. doi: 10.63463/kjes1137

HARVARD

yassen, K., Abass, H., Hameed, A. (2024). 'Advancements in Human Activity Recognition: A Comprehensive Survey of Sensor-Based and Vision-Based Approaches', Kerbala Journal for Engineering Sciences, 4(3), pp. 203-234. doi: 10.63463/kjes1137

VANCOUVER

yassen, K., Abass, H., Hameed, A. Advancements in Human Activity Recognition: A Comprehensive Survey of Sensor-Based and Vision-Based Approaches. Kerbala Journal for Engineering Sciences, 2024; 4(3): 203-234. doi: 10.63463/kjes1137

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