A Novel Integration of Face-Recognition Algorithms with a Soft Voting Scheme for Efficiently Tracking Missing Person in Challenging Large-Gathering Scenarios

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 f...

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Vydané v:Sensors (Basel, Switzerland) Ročník 22; číslo 3; s. 1153
Hlavní autori: Nadeem, Adnan, Ashraf, Muhammad, Rizwan, Kashif, Qadeer, Nauman, AlZahrani, Ali, Mehmood, Amir, Abbasi, Qammer H.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Switzerland MDPI AG 03.02.2022
MDPI
Predmet:
Accuracy
Algorithms
Analysis
Automation
Cameras
Child
Datasets
Face
Facial Recognition
Facial recognition technology
Humans
integration of face-recognition algorithms
large-crowd gatherings
Missing persons
Mosques
Politics
Social networks
soft voting scheme
tracking missing persons
Voting
United States > US
large-crowd gatherings
soft voting scheme
integration of face-recognition algorithms
tracking missing persons
ISSN:1424-8220, 1424-8220
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Shrnutí: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.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s22031153