Computers 2013, 2(2), 88-131; doi:10.3390/computers2020088
Review

A Review on Video-Based Human Activity Recognition

1,* email, 2email, 1email, 1email, 3email and 4email
Received: 29 November 2012; in revised form: 21 February 2013 / Accepted: 30 April 2013 / Published: 5 June 2013
(This article belongs to the Special Issue Activity Detection and Novel Sensing Technologies)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: This review article surveys extensively the current progresses made toward video-based human activity recognition. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. In the core technology, three critical processing stages are thoroughly discussed mainly: human object segmentation, feature extraction and representation, activity detection and classification algorithms. In the human activity recognition systems, three main types are mentioned, including single person activity recognition, multiple people interaction and crowd behavior, and abnormal activity recognition. Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems. Our survey, which aims to provide a comprehensive state-of-the-art review of the field, also addresses several challenges associated with these systems and applications. Moreover, in this survey, various applications are discussed in great detail, specifically, a survey on the applications in healthcare monitoring systems.
Keywords: human activity recognition; segmentation; feature representation; security surveillance; healthcare monitoring; human computer interface
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MDPI and ACS Style

Ke, S.-R.; Thuc, H.L.U.; Lee, Y.-J.; Hwang, J.-N.; Yoo, J.-H.; Choi, K.-H. A Review on Video-Based Human Activity Recognition. Computers 2013, 2, 88-131.

AMA Style

Ke S-R, Thuc HLU, Lee Y-J, Hwang J-N, Yoo J-H, Choi K-H. A Review on Video-Based Human Activity Recognition. Computers. 2013; 2(2):88-131.

Chicago/Turabian Style

Ke, Shian-Ru; Thuc, Hoang L.U.; Lee, Yong-Jin; Hwang, Jenq-Neng; Yoo, Jang-Hee; Choi, Kyoung-Ho. 2013. "A Review on Video-Based Human Activity Recognition." Computers 2, no. 2: 88-131.

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