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Neural Computing and Applications
Published in: Neural Computing and Applications 5/2023

20-10-2022 | Original Article

Toward human activity recognition: a survey

Authors: Gulshan Saleem, Usama Ijaz Bajwa, Rana Hammad Raza

Published in: Neural Computing and Applications | Issue 5/2023

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Abstract

Human activity recognition (HAR) is a complex and multifaceted problem. The research community has reported numerous approaches to perform HAR. Along with HAR approaches, various surveys have revealed HAR trends in various environments and applications. HAR is linked to a variety of technology-dependent daily life systems, such as human–computer interaction systems, security surveillance, video surveillance, healthcare surveillance, robotics, content-based information retrieval, and monitoring systems. Because of technological advancements, HAR trends change quickly and necessitate an up-to-date and broader perspective. This study offers an HAR taxonomy, which includes online/offline HAR, multimodal/unimodal HAR, handcrafted feature-based, and learning-based approaches. This study attempts to present the multidisciplinary nature of HAR, such as application areas, activity types, task complexities, benchmark datasets, and/methods. This research includes a comparative analysis of state-of-the-art HAR methods and a discussion of popular datasets. The selected studies have been categorized using taxonomy, and different attributes such as activity complexity, dataset size, and recognition rate have been used for their analysis. The comparative analysis of HAR approaches has also helped to highlight domain challenges and open research directions for HAR researchers to follow.
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Metadata
Title
Toward human activity recognition: a survey
Authors
Gulshan Saleem
Usama Ijaz Bajwa
Rana Hammad Raza
Publication date
20-10-2022
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 5/2023
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-022-07937-4

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