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Erschienen in:
2019 | OriginalPaper | Buchkapitel
Attendance and Security System Based on Building Video Surveillance
verfasst von : Kailai Sun, Qianchuan Zhao, Jianhong Zou, Xiaoteng Ma
Erschienen in: Advancements in Smart City and Intelligent Building
Verlag: Springer Singapore
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Abstract
The attendance system plays a very important role in the modern enterprise’s operation, and the security of the building has always been a matter of concern to the people. Based on networked surveillance video, this paper integrates the attendance and security functions and fuses video image processing, deep learning, and face recognition to design an intelligent attendance and security system. We propose a sliding average method to identify persons’ identities. The experimental results verify the effectiveness of our method. The false reject rate (FRR) in our system reaches 0.51%, the false accept rate (FAR) reaches 2.52%, and the correct identification rate reaches 98.85%. The system is applied to some video surveillance areas, with advantages of nonintrusive, passive attendance and multiple persons’ attendance at the same time.