title: The mask detection technology for occluded face analysis in the surveillance system.
abstract: The surveillance systems have been widely used in automatic teller machines (ATMs), banks, convenient stores, etc. For example, when a customer uses the ATM, the surveillance systems will record his/her face information. The information will help us understand and trace who withdrew money. However, when criminals use the ATM to withdraw illegal money, they usually block their faces with something (in Taiwan, criminals usually use safety helmets or masks to block their faces). That will degrade the purpose of the surveillance system. In previous work, we already proposed a technology for safety helmet detection. In this paper, we propose a mask detection technology based upon automatic face recognition methods. We use the Gabor filters to generate facial features and utilize geometric analysis algorithms for mask detection. The technology can give an early warning to save-guards when any "customer" or "intruder" blocks his/her face information with a mask. Besides, the technology can assist face detection in the automatic face recognition system. Experimental results show the performance and reliability of the proposed technology.
authors.affiliation: Department of Forensic Science, Central Police University, Taoyuan, Taiwan. cwen@mail.cpu.edu.tw
authors.forename: Che-Yen
authors.initials: CY
authors.lastname: Wen
authors.forename: Shih-Hsuan
authors.initials: SH
authors.lastname: Chiu
authors.forename: Yi-Ren
authors.initials: YR
authors.lastname: Tseng
authors.forename: Chuan-Pin
authors.initials: CP
authors.lastname: Lu
mesh_terms: D003415:Crime / Q000517:prevention & control*; D005145:Face; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D010363:Pattern Recognition, Automated; D010470:Perceptual Masking; D010781:Photography