Deep learning based face liveness detection in videos
作者： Yaman Akbulut , Abdulkadir Sengur , Umit Budak , Sami Ekici
DOI: 10.1109/IDAP.2017.8090202
关键词: Face (geometry) 、 Artificial intelligence 、 Computer science 、 Face detection 、 Liveness 、 Object-class detection 、 Biometrics 、 Pooling 、 Feature (computer vision) 、 Computer vision 、 Deep learning
摘要: The human face is an important biometric quantity which can be used to access a user-based system. As images easily obtained via mobile cameras and social networks, systems should robust against spoof attacks. In other words, reliable face-based system determine both the identity liveness of input face. To this end, various feature-based detection methods have been proposed. These generally apply series processes image(s) in order detect paper, deep-learning-based Two different deep learning models are achieve this, namely local receptive fields (LRF)-ELM CNN. LRF-ELM recently developed model contains convolution pooling layer before fully connected that makes fast. CNN, however, layers. addition, CNN may more A experiments were conducted on two popular databases, NUAA CASIA. results then compared, method yielded better databases.
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