Face Recognition and Tracking of Missing Person using AI

In the world, a countless number of people including kids, teens, old-aged people are missing every day. Most of them remain untraced. Tragically, the majority of these cases remain unresolved. Missing persons face numerous dangers, with some becoming victims of death, rape, or abuse. The uncertainty surrounding their fate exposes concerned individuals such as parents, friends, relatives, and guardians to significant stress and worry. This study proposes a system designed to aid both the police and the public by accelerating the search process through the implementation of face recognition technology. A comparative study conducted with other models, including MTCNN, SSD, and Haar Cascades, demonstrates YOLOv8's superior real-time performance and accuracy. The system incorporates a collaborative public-police alert mechanism and offers a scalable solution suitable for implementation in large-scale urban environments. Testing of the system reveals a recognition accuracy of 94% with a detection time of approximately 40 milliseconds per frame.

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Publication Details

Journal
Journal of Trends in Computer Science and Smart Technology
Published
2025-04-21
DOI
https://doi.org/10.36548/jtcsst.2025.1.002
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Face Recognition and Tracking of Missing Person using AI

Mohammed Ali, T. Aswani, Семикопенко Г.П., Gorli Lakshmi Sai Amalodbhavi et al.
Journal of Trends in Computer Science and Smart Technology
Face recognition and analysis
article

Face Recognition and Tracking of Missing Person using AI

Mohammed Ali, T. Aswani, Семикопенко Г.П., Gorli Lakshmi Sai Amalodbhavi, Pindiga Urmila
article en

Abstract

In the world, a countless number of people including kids, teens, old-aged people are missing every day. Most of them remain untraced. Tragically, the majority of these cases remain unresolved. Missing persons face numerous dangers, with some becoming victims of death, rape, or abuse. The uncertainty surrounding their fate exposes concerned individuals such as parents, friends, relatives, and guardians to significant stress and worry. This study proposes a system designed to aid both the police and the public by accelerating the search process through the implementation of face recognition technology. A comparative study conducted with other models, including MTCNN, SSD, and Haar Cascades, demonstrates YOLOv8's superior real-time performance and accuracy. The system incorporates a collaborative public-police alert mechanism and offers a scalable solution suitable for implementation in large-scale urban environments. Testing of the system reveals a recognition accuracy of 94% with a detection time of approximately 40 milliseconds per frame.

Journal of Trends in Computer Science and Smart TechnologyVol. 7(1)
Jawaharlal Nehru Technological University, Hyderabad (IN), English and Foreign Languages University (IN)
Openalex Percentile: Top 93%
Face recognition and analysis
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