University of Oulu

Beddiar, D.R., Nini, B., Sabokrou, M. et al. Vision-based human activity recognition: a survey. Multimed Tools Appl 79, 30509–30555 (2020). https://doi.org/10.1007/s11042-020-09004-3

Vision-based human activity recognition : a survey

Saved in:
Author: Beddiar, Djamila Romaissa1,2; Nini, Brahim1; Sabokrou, Mohammad3;
Organizations: 1Research Laboratory on Computer Science’s Complex Systems, Larbi Ben M’hidi University, Oum El Bouaghi, Algeria
2Center for Machine Vision Research, Computer Science and Engineering, University of Oulu, Oulu, Finland
3School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Tehran Province, Iran
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020112392286
Language: English
Published: Springer Nature, 2020
Publish Date: 2020-11-23
Description:

Abstract

Human activity recognition (HAR) systems attempt to automatically identify and analyze human activities using acquired information from various types of sensors. Although several extensive review papers have already been published in the general HAR topics, the growing technologies in the field as well as the multi-disciplinary nature of HAR prompt the need for constant updates in the field. In this respect, this paper attempts to review and summarize the progress of HAR systems from the computer vision perspective. Indeed, most computer vision applications such as human computer interaction, virtual reality, security, video surveillance and home monitoring are highly correlated to HAR tasks. This establishes new trend and milestone in the development cycle of HAR systems. Therefore, the current survey aims to provide the reader with an up to date analysis of vision-based HAR related literature and recent progress in the field. At the same time, it will highlight the main challenges and future directions.

see all

Series: Multimedia tools and applications
ISSN: 1380-7501
ISSN-E: 1573-7721
ISSN-L: 1380-7501
Volume: 79
Issue: 41-42
Pages: 30509 - 30555
DOI: 10.1007/s11042-020-09004-3
OADOI: https://oadoi.org/10.1007/s11042-020-09004-3
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Subjects:
Funding: Open access funding provided by University of Oulu including Oulu University Hospital.
Copyright information: © The Authors 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
  https://creativecommons.org/licenses/by/4.0/