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A review on video-based human activity recognition

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dc.contributor.author Shian-Ru `, Ke
dc.contributor.author Hoang, Le Uyen Thuc
dc.contributor.author Yong-Jin, Lee
dc.contributor.author Jenq-Neng, Hwang
dc.contributor.author Kyoung-Ho, Choi
dc.date.accessioned 2021-07-28T14:09:14Z
dc.date.available 2021-07-28T14:09:14Z
dc.date.issued 2013
dc.identifier.issn 23105496
dc.identifier.uri http://hdl.handle.net/123456789/5782
dc.description 44p:, ill. en_US
dc.description.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 en_US
dc.language.iso en en_US
dc.publisher University of Cape Coast en_US
dc.title A review on video-based human activity recognition en_US
dc.type Article en_US


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