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Cited by 2,056

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Human activity analysis: A review

Aggarwal, J.K., Ryoo, M.S.·2011·ACM Computing Surveys
DOI 10.1145/1922649.1922653
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Abstract

Human activity recognition is an important area of computer vision research. Its applications include surveillance systems, patient monitoring systems, and a variety of systems that involve interactions between persons and electronic devices such as human-computer interfaces. Most of these applications require an automated recognition of high-level activities, composed of multiple simple (or atomic) actions of persons. This article provides a detailed overview of various state-of-the-art research papers on human activity recognition. We discuss both the methodologies developed for simple human actions and those for high-level activities. An approach-based taxonomy is chosen that compares the advantages and limitations of each approach. Recognition methodologies for an analysis of the simple actions of a single person are first presented in the article. Space-time volume approaches and sequential approaches that represent and recognize activities directly from input images are discussed. Next, hierarchical recognition methodologies for high-level activities are presented and compared. Statistical approaches, syntactic approaches, and description-based approaches for hierarchical recognition are discussed in the article. In addition, we further discuss the papers on the recognition of human-object interactions and group activities. Public datasets designed for the evaluation of the recognition methodologies are illustrated in our article as well, comparing the methodologies' performances. This review will provide the impetus for future research in more productive areas.

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Cited by

Metadata

Authors
Aggarwal, J. K., & Ryoo, M. S.
Venue
ACM Computing Surveys
Publisher
Association for Computing Machinery (ACM)
Published
2011-04
Volume
43
Issue
3
Pages
1-43
ISSN
  • 0360-0300 (ISSN-L)
  • 1557-7341
DOI
10.1145/1922649.1922653
OpenAlex
W1983705368
Cited by
2,056
References
4
FWCI
177.01
Type
journal article
Language
en
Open access
closed
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Funders
Texas Higher Education Coordinating Board (003658-0140-2007)

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