UPM Institutional Repository

A bibliometric analysis of human action recognition


Aryanfar, Alihossein and Abdul Halin, Alfian and Yaakob, Razali and Sulaiman, Md Nasir and Mohammadpour, Leila (2016) A bibliometric analysis of human action recognition. In: Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016, 21-22 Sept. 2016, London, United Kingdom. (pp. 419-427).


Over the past two decades, the use of computer vision methods for enabling machines to recognize human action from a sequence of images, has grown as information technologies advance, and hardware availability such as cameras (especially closed circuit television) has increased. From the latter part of the 1980s till recently, computer vision has been employed for human action recognition research. Due to the volume of existing academic studies, it would be impractical to review all researches. This paper presents a brief analysis regarding the body of knowledge in Human Activity Recognition from 1987 to 2015. Bibliometric techniques based on the Science Citation Index (SCI) databases of the Web of Science are employed where 1,172 articles are critically analysed on the various aspects of publication characteristics such as authorship, countries, institutions, number of citations, and keywords. The pace of publishing in this field has shown to increase rapidly over last 20 years. By identifying the global trends in HAR research, this study is beneficial for researchers, for example, in the selection of future research topics. Similarly, policy makers can also benefit from the findings for a better understanding of how HAR develops over time.

Download File

A bibliometric analysis of human action recognition.pdf

Download (5kB) | Preview

Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.1007/978-3-319-56994-9_30
Publisher: Springer
Keywords: Human action recognition; Bibliometric analysis; Content analysis; Literature review; Most cited; Research trends
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 30 Apr 2018 01:09
Last Modified: 30 Apr 2018 01:09
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1007/978-3-319-56994-9_30
URI: http://psasir.upm.edu.my/id/eprint/35522
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item