An Automated Surveillance System Based on Multi-Processor and GPU Architecture

Authors

  • M. Ben Ayed AlGhat College of Science and Humanities, Al Majmaah University, Saudi Arabia | University of Sfax, Tunisia
  • S. Elkosantini College of Engineering, King Saud University, Saudi Arabia
  • M. Abid Sfax National School of Engineers, University of Sfax, Tunisia
Volume: 7 | Issue: 6 | Pages: 2319-2323 | December 2017 | https://doi.org/10.48084/etasr.1645

Abstract

Video surveillance systems are a powerful tool applied in various systems. Traditional systems based on human vision are to be avoided due to human errors. An automated surveillance system based on suspicious behavior presents a great challenge to developers. Such detection is a rather complex procedure and also a rather time-consuming one. An abnormal behavior could be identified by: actions, faces, route, etc. The definition of the characteristics of an abnormal behavior still present a big problem. This paper proposes a specific architecture for a surveillance system. The aim is to accelerate the system and obtain a reliable and accelerated suspicious behavior recognition. Finally, the experiment section illustrates the results with comparison of some of the most recent approaches.

Keywords:

Surveillance system, suspicious behaviors, multi-processor, GPU

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How to Cite

[1]
M. Ben Ayed, S. Elkosantini, and M. Abid, “An Automated Surveillance System Based on Multi-Processor and GPU Architecture”, Eng. Technol. Appl. Sci. Res., vol. 7, no. 6, pp. 2319–2323, Dec. 2017.

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