File(s) under permanent embargo

Reason: This item is currently closed access.

Multi-agent based framework for person re-identification in video surveillance

conference contribution
posted on 10.03.2017, 14:51 by Muna S. Al-Rahbi, Eran Edirisinghe, Syeda FatimaSyeda Fatima
Multi-agent based systems have been used in a number of practical application domains. However their use in computer vision based systems that often provide solutions to automated video surveillance, remains in its infancy. Addressing this gap in research this paper proposes a novel design, based on multi-agents, to address one of the most important open research problems in video surveillance, i.e. person re-identification. The re-design of a typical computer vision based solution for the problem is based on our analysis of the problem considering how a human observer would successfully carry out person re-identification. Hence the proposed approach mimics human behavior and promises many advantages over the existing approaches that do not consider such a human behavior based approach. We provide preliminary experimental results to justify the contribution of the proposed novel approach to person re-identification and conclude the paper with insights to future research that has potential for a new paradigm of research in person re-identification in video surveillance.

History

School

  • Science

Department

  • Computer Science

Published in

Future technologies conference

Pages

1349 - 1352 (4)

Citation

AL-RAHBI, M.S., EDIRISINGHE, E.A. and FATIMA, S., 2017. Multi-agent based framework for person re-identification in video surveillance. Future Technologies Conference (FTC), San Francisco, USA, 6th-7th December 2016, pp. 1349-1352.

Publisher

© IEEE

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

13/09/2016

Publication date

2017

Notes

This paper is closed access.

ISBN

9781509041718

Language

en

Location

San Francisco