A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets
Year: 2019
Type: review
Study design: Systematic Review
Abstract: Video surveillance systems obtain a great interest as application-oriented studies that have been growing rapidly in the past decade. The most recent studies attempt to integrate computer vision, image processing, and artificial intelligence capabilities into video surveillance applications. Although there are so many achievements in the acquisition of datasets, methods, and frameworks published, there are not many papers that can provide a comprehensive picture of the current state of video surveillance system research. This paper provides a comprehensive and systematic review on the literature from various video surveillance system studies published from 2010 through 2019. Within a selected study extraction process, 220 journal-based publications were identified and analyzed to illustrate the research trends, datasets, methods, and frameworks used in the field of video surveillance, to provide an in-depth explanation about research trends that many topics raised by researchers as a focus in their researches, to provide references on public datasets that are often used by researchers as a comparison and a means of developing a test method, and to give accounts on the improvement and integration of network infrastructure design to meet the demand for multimedia data. In the end of this paper, several opportunities and challenges related to researches in the video surveillance system are mentioned.
Source: IEEE Access
Institution: Universitas Dian Nuswantoro
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,750
OpenAlex ID: W2992009433