Monitors Replay Attack Dataset

Key Features of the Dataset:

1. Replay Attacks:
   • Videos showcasing real people replayed on computer screens, filmed using a mobile phone.
   • Captures a variety of replay scenarios to provide a realistic representation of potential spoofing attempts.
2. Diverse Collection:
   • Includes videos of genuine individuals presenting spoof attacks with varying resolutions, views, and colors.
   • Ensures a comprehensive dataset covering different conditions and setups.
3. Novel Anti-Spoofing Approach:
   • The dataset supports the development of novel approaches to learn and detect spoofing techniques.
   • Focuses on extracting features from genuine facial images to prevent unauthorized access by fake users.
4. Variety in Facial Presentations:
   • Contains images and videos of real humans with multiple facial presentations.
   • Aids in developing algorithms capable of distinguishing between real and spoofed biometric data.
5. Research and Development:
   • Serves as a valuable resource for researchers working on biometric security, particularly in developing techniques to counteract replay attacks.
   • Supports advancements in machine learning models for facial recognition and anti-spoofing technologies.