Tracking missing person in large crowd gathering using intelligent video surveillance

Nadeem, A., Ashraf, M., Qadeer, N., Rizwan, K., Mehmood, A., Al Zahrani, A., Noor, F. and Abbasi, Q. H. (2022) Tracking missing person in large crowd gathering using intelligent video surveillance. Sensors, 22(14), 5270. (doi: 10.3390/s22145270)

Abstract

Locating a missing child or elderly person in a large gathering through face recognition in videos is still challenging because of various dynamic factors. In this paper, we present an intelligent mechanism for tracking missing persons in an unconstrained large gathering scenario of Al-Nabawi Mosque, Madinah, KSA. The proposed mechanism in this paper is unique in two aspects. First, there are various proposals existing in the literature that deal with face detection and recognition in high-quality images of a large crowd but none of them tested tracking of a missing person in low resolution images of a large gathering scenario. Secondly, our proposed mechanism is unique in the sense that it employs four phases: (a) report missing person online through web and mobile app based on spatio-temporal features; (b) geo fence set estimation for reducing search space; (c) face detection using the fusion of Viola Jones cascades LBP, CART, and HAAR to optimize the results of the localization of face regions; and (d) face recognition to find a missing person based on the profile image of reported missing person. The overall results of our proposed intelligent tracking mechanism suggest good performance when tested on a challenging dataset of 2208 low resolution images of large crowd gathering.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Abbasi, Professor Qammer
• Authors: Nadeem, A., Ashraf, M., Qadeer, N., Rizwan, K., Mehmood, A., Al Zahrani, A., Noor, F., and Abbasi, Q. H.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Journal Name: Sensors
• Publisher: MDPI
• ISSN: 1424-8220
• ISSN (Online): 1424-8220
• Published Online: 14 July 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Sensors 22(14):5270
• Publisher Policy: Reproduced under a Creative Commons licence