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A survey and taxonomy on intelligent surveillance from a system perspective

Published online by Cambridge University Press:  25 April 2018

Radu-Casian Mihailescu ,
Paul Davidsson ,
Ulrik Eklund  and
Jan A. Persson
Radu-Casian Mihailescu
Affiliation:
Department of Computer Science, Malmö University, Internet of Things and People Research Center, 205 06 Malmö, Sweden e-mail: [email protected], [email protected], [email protected], [email protected]
Paul Davidsson
Affiliation:
Department of Computer Science, Malmö University, Internet of Things and People Research Center, 205 06 Malmö, Sweden e-mail: [email protected], [email protected], [email protected], [email protected]
Ulrik Eklund
Affiliation:
Department of Computer Science, Malmö University, Internet of Things and People Research Center, 205 06 Malmö, Sweden e-mail: [email protected], [email protected], [email protected], [email protected]
Jan A. Persson
Affiliation:
Department of Computer Science, Malmö University, Internet of Things and People Research Center, 205 06 Malmö, Sweden e-mail: [email protected], [email protected], [email protected], [email protected]
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Abstract

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.

Type
Principles and Practice of Multi-Agent Systems
Information
The Knowledge Engineering Review , Volume 33 , 2018 , e4
Copyright
© Cambridge University Press, 2018 

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