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Tytuł pozycji:

A novel technique for automated concealed face detection in surveillance videos.

Tytuł :
A novel technique for automated concealed face detection in surveillance videos.
Autorzy :
Hosni Mahmoud HA; Department of Computer Science, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.; Department of Computer and Systems Engineering, Faculty of Engineering, University of Alexandria, Alexandria, Egypt.
Mengash HA; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
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Źródło :
Personal and ubiquitous computing [Pers Ubiquitous Comput] 2020 Jun 12, pp. 1-12. Date of Electronic Publication: 2020 Jun 12.
Publication Model :
Ahead of Print
Typ publikacji :
Journal Article
Język :
English
Imprint Name(s) :
Original Publication: Godalming, UK : Springer-Verlag London Ltd., [2001]-
References :
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Contributed Indexing :
Keywords: Face detection; Human skin detection; Security; YCbCr space color
Entry Date(s) :
Date Created: 20200825 Latest Revision: 20200928
Update Code :
20210623
PubMed Central ID :
PMC7292477
DOI :
10.1007/s00779-020-01419-x
PMID :
32837499
Czasopismo naukowe
Face detection perceives great importance in surveillance paradigm and security paradigm areas. Face recognition is the technique to identify a person identity after face detection. Extensive research has been done on these topics. Another important research problem is to detect concealed faces, especially in high-security places like airports or crowded places like concerts and shopping centres, for they may prevail security threat. Also, in order to help effectively in preventing the spread of Coronavirus, people should wear masks during the pandemic especially in the entrance to hospitals and medical facilities. Surveillance systems in medical facilities should issue warnings against unmasked people. This paper presents a novel technique for concealed face detection based on complexion detection to challenge a concealed face assumption. The proposed algorithm first determine of the existence of a human being in the surveillance scene. Head and shoulder contour will be detected. The face will be clustered to cluster patches. Then determination of presence or absent of human skin will be determined. We proposed a hybrid approach that combines normalized RGB (rgb) and the YCbCr space color. This technique is tested on two datasets; the first one contains 650 images of skin patches. The second dataset contains 800 face images. The algorithm achieves an average detection rate of 97.51% for concealed faces. Also, it achieved a run time comparable with existing state-of-the-art concealed face detection systems that run in real time.
(© Springer-Verlag London Ltd., part of Springer Nature 2020.)

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