White Paper - Facial Recognition Under the Microscope

In this document we look at some of the real-life issues that everybody faces when using artificial intelligence in a facial recognition environment. Artificial Intelligence is a term that is very current and topical. So, we are going to try and look under the hood at some of the things that are actually AI and how to utilise artificial intelligence for Automatic Facial Recognition (AFR).

Based on a seminar presentation at The Security Event featuring: John Downie - Sales Director Visual Management Systems Ltd., Professor Jeremy Levesley - Department of Mathematics, Leicester University with contributions from Professor Ivan Tyukin Leicester University.

At the outset we will need to establish exactly what AFR means in the context of this document. The role of AFR in the application we are discussing is that of detection and identification whereby faces are detected in a multi subject environment and matched with a known pool of individuals be they “the bad guys” or VIPs.

Topics covered:

• Back to Basics.. the truth about Artificial Intelligence
• What to look for in a facial recognition system
• Real-time facial detection
• High speed facial data processing
• High performance matching engines
• Machine learning capability
• Client specified matching criteria
• Digital tagging and ease-of-use
• False positives and how to combat them
• GDPR and facial recognition
• Who will benefit from accurate multi-subject AFR
• TITAN AI a practical and proven solution