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A survey and taxonomy on intelligent surveillance from a system perspective
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-0998-6585
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
Malmö University, Internet of Things and People (IOTAP). Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-9471-8405
2018 (English)In: Knowledge engineering review (Print), ISSN 0269-8889, E-ISSN 1469-8005, Vol. 33, article id e4Article in journal (Refereed) Published
Abstract [en]

Recent proliferation of surveillance systems is mostly attributed to advances in both image-processing techniques and hardware enhancement of smart cameras, as well as the ubiquity of sensor-driven architectures. Owing to these capabilities, new aspects are coming to the forefront. This paper addresses the current state-of-the-art and provides researchers with an overview of existing surveillance solutions, analyzing their properties as a system and drawing attention to relevant challenges when developing, deploying and managing them. Also, some of the more prominent application domains are highlighted here. In an effort to understand the development of the advanced solutions, based on their most distinctive characteristics, we propose a taxonomy for surveillance systems to help classify them and reveal gaps in existing research. We conclude by identifying promising future research lines.

Place, publisher, year, edition, pages
Cambridge University Press, 2018. Vol. 33, article id e4
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-16040DOI: 10.1017/S0269888918000048ISI: 000450970900001Scopus ID: 2-s2.0-85060530281Local ID: 25003OAI: oai:DiVA.org:mau-16040DiVA, id: diva2:1419562
Available from: 2020-03-30 Created: 2020-03-30 Last updated: 2024-02-05Bibliographically approved

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Publisher's full textScopushttps://www.cambridge.org/core/journals/knowledge-engineering-review/article/survey-and-taxonomy-on-intelligent-surveillance-from-a-system-perspective/806CA2982C64CF685044831A7FF6A2A5

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Mihailescu, Radu-CasianDavidsson, PaulEklund, UlrikPersson, Jan A.

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