Live Face Verification with Multiple Instantialized Local Homographic Parameterization

Live Face Verification with Multiple Instantialized Local Homographic Parameterization

Chen Lin, Zhouyingcheng Liao, Peng Zhou, Jianguo Hu, Bingbing Ni

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Main track. Pages 814-820. https://doi.org/10.24963/ijcai.2018/113

State-of-the-art live face verification methods would easily be attacked by recorded facial expression sequence. This work directly addresses this issue via proposing a patch-wise motion parameterization based verification network infrastructure. This method directly explores the underlying subtle motion difference between the facial movements re-captured from a planer screen (e.g., a pad) and those from a real face; therefore interactive facial expression is no longer required. Furthermore, inspired by the fact that ?a fake facial movement sequence MUST contains many patch-wise fake sequences?, we embed our network into a multiple instance learning framework, which further enhance the recall rate of the proposed technique. Extensive experimental results on several face benchmarks well demonstrate the superior performance of our method.
Keywords:
Computer Vision: Biometrics, Face and Gesture Recognition
Machine Learning Applications: Other Applications