Interactive Photo Liveness for Presentation Attacks Detection
This paper presents an interactive liveness detection approach
against presentation attacks. It aims to minimize the impact on the
user, who is only asked to produce single head movements. The described
approach combines two methods: (1) single-photo liveness estimation
based on CNN implementation, and (2) interactive liveness estimation
based on head movements detected from two video frames extracted
before and during the movement. The resulting system is designed to
work on smartphones and by web-cameras. An appropriate database was
collected for experiments. These achieved EER of less than 5% for paper
spoofing attacks, less than 4% for monitor and 0.6% for tablet, while the
Failure to Capture (FTC) was less than 3% for the most user-friendly
scenario.