A novel integration of face-recognition algorithms with a soft voting scheme for efficiently tracking missing person in challenging large-gathering scenarios

Nadeem, A., Ashraf, M., Rizwan, K., Qadeer, N., AlZahrani, A., Mehmood, A. and Abbasi, Q. H. (2022) A novel integration of face-recognition algorithms with a soft voting scheme for efficiently tracking missing person in challenging large-gathering scenarios. Sensors, 22(3), 1153. (doi: 10.3390/s22031153)

Abstract

The probability of losing vulnerable companions, such as children or older ones, in large gatherings is high, and their tracking is challenging. We proposed a novel integration of face-recognition algorithms with a soft voting scheme, which was applied, on low-resolution cropped images of detected faces, in order to locate missing persons in a challenging large-crowd gathering. We considered the large-crowd gathering scenarios at Al Nabvi mosque Madinah. It is a highly uncontrolled environment with a low-resolution-images data set gathered from moving cameras. The proposed model first performs real-time face-detection from camera-captured images, and then it uses the missing person’s profile face image and applies well-known face-recognition algorithms for personal identification, and their predictions are further combined to obtain more mature prediction. The presence of a missing person is determined by a small set of consecutive frames. The novelty of this work lies in using several recognition algorithms in parallel and combining their predictions by a unique soft-voting scheme, which in return not only provides a mature prediction with spatio-temporal values but also mitigates the false results of individual recognition algorithms. The experimental results of our model showed reasonably good accuracy of missing person’s identification in an extremely challenging large-gathering scenario.

• Item Type: Articles
• Additional Information: This research was supported by the Deanship of Scientific Research, Islamic University of Madinah, Madinah (KSA), under Tammayuz program grant number 1442/505.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Abbasi, Professor Qammer

Creator Roles

Abbasi, Q. A.: Validation, Formal analysis, Writing – review and editing

• Authors: Nadeem, A., Ashraf, M., Rizwan, K., Qadeer, N., AlZahrani, A., Mehmood, A., 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: 03 February 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Sensors 22(3): 1153
• Publisher Policy: Reproduced under a Creative Commons licence