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利用智能视频监控追踪大型人群聚集中的失踪人员

Tracking Missing Person in Large Crowd Gathering Using Intelligent Video Surveillance.

机构信息

Faculty of Computer and Information System, Islamic University of Madinah, Madinah 42351, Saudi Arabia.

Department of Physics, Federal Urdu University of Arts, Science & Technology, Karachi 75300, Pakistan.

出版信息

Sensors (Basel). 2022 Jul 14;22(14):5270. doi: 10.3390/s22145270.

DOI:10.3390/s22145270
PMID:35890950
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9323688/
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.

摘要

在大型集会中通过视频进行人脸识别来定位失踪的儿童或老人仍然具有挑战性，因为存在各种动态因素。在本文中，我们提出了一种在沙特麦地那先知清真寺无约束的大型集会场景中跟踪失踪人员的智能机制。本文提出的机制在两个方面具有独特性。首先，文献中存在各种处理大人群高质量图像中的人脸检测和识别的提案，但没有一个提案测试在低分辨率的大型集会场景图像中跟踪失踪人员。其次，我们提出的机制在以下方面具有独特性：（a）通过基于时空特征的网络和移动应用程序在线报告失踪人员；（b）设置地理围栏估计以缩小搜索空间；（c）使用融合 Viola Jones 级联 LBP、CART 和 HAAR 的方法进行人脸检测，以优化人脸区域定位的结果；（d）基于报告的失踪人员的个人资料图像进行人脸识别以找到失踪人员。当在具有挑战性的 2208 张大型人群聚集的低分辨率图像数据集上进行测试时，我们提出的智能跟踪机制的整体结果表明具有良好的性能。

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本文引用的文献

1
A Novel Integration of Face-Recognition Algorithms with a Soft Voting Scheme for Efficiently Tracking Missing Person in Challenging Large-Gathering Scenarios.一种新颖的人脸识别算法与软投票方案的集成，用于在具有挑战性的大规模集会场景中高效跟踪失踪人员。
Sensors (Basel). 2022 Feb 3;22(3):1153. doi: 10.3390/s22031153.
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Efficient Face Recognition System for Operating in Unconstrained Environments.用于在无约束环境中运行的高效人脸识别系统。
J Imaging. 2021 Aug 26;7(9):161. doi: 10.3390/jimaging7090161.
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Searching for a face in the crowd: Pitfalls and unexplored possibilities.
在人群中寻找一张面孔：陷阱与未被探索的可能性。
Atten Percept Psychophys. 2020 Feb;82(2):626-636. doi: 10.3758/s13414-020-01975-7.
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Proc Natl Acad Sci U S A. 2018 Jun 12;115(24):6171-6176. doi: 10.1073/pnas.1721355115. Epub 2018 May 29.