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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Vydáno v:	Sensors (Basel, Switzerland) Ročník 22; číslo 3; s. 1153
Hlavní autoři:	Nadeem, Adnan, Ashraf, Muhammad, Rizwan, Kashif, Qadeer, Nauman, AlZahrani, Ali, Mehmood, Amir, Abbasi, Qammer H.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 03.02.2022 MDPI
Témata:	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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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.
AbstractList	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. 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.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.
Audience	Academic
Author	AlZahrani, Ali Rizwan, Kashif Mehmood, Amir Nadeem, Adnan Abbasi, Qammer H. Ashraf, Muhammad Qadeer, Nauman
AuthorAffiliation	1 Faculty of Computer and Information System, Islamic University of Madinah, Madinah 42351, Saudi Arabia; a.alzahrani@iu.edu.sa 3 Department of Software Engineering, Faculty of Engineering, Science, Technology and Management, Ziauddin University, Karachi 74700, Pakistan; amir.mehmood@zu.edu.pk 2 Department of Computer Science, Federal Urdu University of Arts, Science & Technology, Islamabad 45570, Pakistan; m.ashraf@fuuast.edu.pk (M.A.); kashifrizwan@fuuast.edu.pk (K.R.); nauman.qadeer@fuuast.edu.pk (N.Q.) 4 James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK; qammer.abbasi@glasgow.ac.uk
AuthorAffiliation_xml	– name: 3 Department of Software Engineering, Faculty of Engineering, Science, Technology and Management, Ziauddin University, Karachi 74700, Pakistan; amir.mehmood@zu.edu.pk – name: 4 James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK; qammer.abbasi@glasgow.ac.uk – name: 1 Faculty of Computer and Information System, Islamic University of Madinah, Madinah 42351, Saudi Arabia; a.alzahrani@iu.edu.sa – name: 2 Department of Computer Science, Federal Urdu University of Arts, Science & Technology, Islamabad 45570, Pakistan; m.ashraf@fuuast.edu.pk (M.A.); kashifrizwan@fuuast.edu.pk (K.R.); nauman.qadeer@fuuast.edu.pk (N.Q.)
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SubjectTerms	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
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Title	A Novel Integration of Face-Recognition Algorithms with a Soft Voting Scheme for Efficiently Tracking Missing Person in Challenging Large-Gathering Scenarios
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