There is a misconception that law enforcement agencies in the U.S. use automated face recognition to actively surveil public spaces. Such a dragnet of mass real-time identification and surveillance would be a violation of the Fourth Amendment to the United States...
Step #1: Understand your application Common face recognition applications include forensic search, real-time screening, identity deduplication, and access control. Each application will involve different types of facial imagery (constrained or unconstrained) and will...
Suppose you were offered a futuristic virtual reality system on par with The Matrix for just $100. You would purchase it, right?! Now imagine you needed 50,000 sq. ft. of space in your home to run the system. That would change the proposition quite a bit. In many ways...
Perhaps no technology is improving as rapidly as automated face recognition. For example, over the last four years Rank One has reduced the False Non-Match Rate of our algorithm by over 50x:Other face recognition vendors are similarly improving their accuracy at a...
On Thursday, November 29th, 2018, I presented this topic at the National Institute of Standards and Technology (NIST) International Face Performance Conference (IFPC) in Gaithersburg, MD. “And suddenly, face recognition technology was everywhere…”...
One of many critical considerations when selecting a face recognition SDK or system is the accuracy of the underlying algorithm. Even though an algorithm may meet your hardware requirements, licensing budget, support needs, or other decisive factors, if it is not...
