A Countermeasure against Face-Spoofing Attacks Using an Interaction Video Framework
With an increase in acceptance of face recognition systems,the desire for accurate biometric authentication-face recognition,has increased.Nowadays,the fundamental limitations of existing systems are,the vulnerabilities of false verification via a picture or simple video of a person.In this paper,it is inspired by how humans can perform reliable spoofing detection only based on the available scene and context information.We propose our framework in a combination of interaction model and Moire pattern analysis to make sure that a user is a real person.It is different from some systems that use hardware-based liveness detection.We focus on the software-based approaches,in particular,the necessary algorithms that allow for a liveness detection in real-time.Our experiments results show excellent performance to the state of the art.
Face Recognition Spoofing Attacks Liveness Detection Moving Object Tracking Moir′e Pattern Analysis
Kam Kong Xiali Hei Ting Zeng Caijin Ling Chao Zhang Binheng Song Hui Cao Michael Peays
Dept.of CIS Delaware State University Dover,DE 19901,USA School of EIE Heyuan Polytechnic Heyuan,Guangdong 517000,China Dept.of Math Delaware State University Dover,DE 19901,USA Graduate School at Shenzhen Tsinghua University Shenzhen,518055,China Dept.of EE Xian Jiaotong University Xian,Shaanxi 710049,China
国际会议
重庆
英文
758-763
2017-10-03（万方平台首次上网日期，不代表论文的发表时间）