Video surveillance systems-current status and future trends

Journal article

Tsakanikas, V. and Dagiuklas, A. (2018). Video surveillance systems-current status and future trends. Computers and Electrical Engineering. 70, pp. 736-753. https://doi.org/10.1016/j.compeleceng.2017.11.011
AuthorsTsakanikas, V. and Dagiuklas, A.
Abstract

Within this survey an attempt is made to document the present status of video surveillance systems. The main components of a surveillance system are presented and studied thoroughly. Algorithms for image enhancement, object detection, object tracking, object recognition and item re-identification are presented. The most common modalities utilized by surveillance systems are discussed, putting emphasis on video, in terms of available resolutions and new imaging approaches, like High Dynamic Range video. The most important features and analytics are presented, along with the most common approaches for image / video quality enhancement. Distributed computational infrastructures are discussed (Cloud, Fog and Edge Computing), describing the advantages and disadvantages of each approach. The most important deep learning algorithms are presented, along with the smart analytics that they utilize. Augmented reality and the role it can play to a surveillance system is reported, just before discussing the challenges and the future trends of surveillance.

Keywordssurveillance systems, edge analytics
Year2018
JournalComputers and Electrical Engineering
Journal citation70, pp. 736-753
PublisherElsevier
ISSN0045-7906
Digital Object Identifier (DOI)https://doi.org/10.1016/j.compeleceng.2017.11.011
Web address (URL)https://www.sciencedirect.com/science/article/abs/pii/S0045790617311813
Publication dates
Online14 Nov 2017
Publication process dates
Accepted08 Nov 2017
Deposited22 Sep 2022
Accepted author manuscript
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Open
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