> face recognition … Coin tossing
The FRVT (Face Recognition Vendor Test) reports are an excellent source to gain an understanding how poorly face recognition really works. Mathematically, 2D face recognition is impossible (you are missing a dimension!). Additionally, recognition is knowledge-based. Much of what
we “see” is actually what our brains interpret into the signal but a machine has only the signal … E.g. it will calculate the distances
between certain features etc. but these are not stable over time and they are affected by many external influences. My thesis has a section
on face recognition which also incorporates the main findings of the last FRVT results. I would recommend you read it in case you are
interested. (see her thesis attached above)

> It reports a time of 90 seconds to do a “one to many” search. That, one assumes, is on the database of 10,000. The report states that the system has been pre-loaded with 118,000 iris
images and 1 million fingerprints. The report, however, does not state which technology has been used for the one-to-many search (to screen out
multiple identities). The time taken to perform the search indicates that they used fingerprinting: it is a public figure that the FBI
fingerprint DB contains 45 million entries and it takes 68 minutes to run an exhaustive search on it. At the same time, with optimised DB
architecture, 1 million IrisCodes can be searched in 1 second. Also, it is native to the nature of the iris recognition algorithms that error
rates do not accumulate with DB size – the algorithms make automatic adjustment to the decision threshold so that performance stays optimal. Again, this is native to iris recognition; error rates will accumulate for other technologies – I can give you the technical background on why that is if you are interested.

I will not allow anyone to shine lights into my dicey eyes.

(While in Africa, I found that all Europeans and other northerners looked alike to local people. It depends on the points of comparison.)