The mask detection technology for occluded face analysis in the surveillance system.
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.
Wen
Che-Yen
CY
Department of Forensic Science, Central Police University, Taoyuan, Taiwan. cwen@mail.cpu.edu.tw
Chiu
Shih-Hsuan
SH
Tseng
Yi-Ren
YR
Lu
Chuan-Pin
CP
D003415:Crime / Q000517:prevention & control*; D005145:Face; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D010363:Pattern Recognition, Automated; D010470:Perceptual Masking; D010781:Photography