Detection, Classsification, Recognition and Identification (DCRI)

Good question. Typically, ppf requirements for face recognition analytics are significantly higher than identification.

Face recognition systems typically use a slightly different pixels metrics. Instead of ppf, they generally cite pixels between the eyes. However, that can be easily converted to ppf. Assuming 2.5 inches between the eyes, multiply the pixel between the eyes metric by ~5. A common facial recognition metric is 35 pixels between the eyes, which means 175ppf.

However, some systems ask for even more. We've seen requirements for 50 pixels between the eyes (e.g., 300ppf, requiring a 1.3MP camera to cover a tiny 4 foot wide FoV).

Indeed, one vendor recently said they can do it with just 22 pixels between the eye, which would be 110ppf, lower than what the Sweden National Lab claims for a human to identify a face.

All that said, computers have much lower tolerance for variation and fuzzy images so expect to provide a lot higher PPF for facial recognition analytics.

Greg, thanks, here's a 2 page overview from FLIR on it :)

I had been looking for a more detailed technical paper but could not find one yet on the Internet that explained it detail how it was designed / determined. Anyone who can find, please share.

The problem I see with the Johnson criteria is the same fundamental one as for any conventional surveillance camera, specifically the subjectivity in saying how much is enough to 'detect' a person.

For instance, here's Vumii's video of detecting at 1.5 pixels.

Maybe my eyesight is gone, but that is incredibly difficult to tell that there is an object there. Even if they could spot someone, the level of eyestrain and difficulty must be severe for anyone trying to do this on an ongoing basis. I have to imagine many people would look at that and say, "I need more details / more pixels on target"

The UK has used a human size/aspect ratio test chart called a Rotakin for testing end-to-end cctv performance for many years. It is a practical method of testing for identificaton criteria. It was developed by the UK Police Scientific Development Branch

A Rotakin testing requirement was written into the UK minimum survellance standards for all licensed CCTV installations although I am not sure if this is still used.

Hello all!
Let me see if I can shed some light on this.

Identify, recognize, detect, etc. come from European standards published in 1996, see http://www.cenelec.eu/dyn/www/f?p=WEB:110:956246286239172::::FSP_PROJECT, FSP_LANG_ID: 5028.25 (do not buy this because it recently (Jan 2012) has been replaced).

From there you can read that the possibility of such identify a person for an operator (i.e. primarily for live viewing) is that the person occupies 120% of the image height (cut off at the knees). And to be able to detect a person is thus about an operator, at the right distance from the monitor, reliably shall be able to detect a person moving in the picture. The prerequisite is that the image resolution is 400 TV lines or more (scanned in the horizontal plane). After these basic requirements, then also lenses, lighting, etc. has to be taken into account. This works quite well.

Regarding Swedish National Lab recommendations then these are actually from - the FBI! Note that these recommendations are really just for commercial establishments (ie indoors). And this gets very messy because it does not comply with European standards (are you still with me?).

By the way, if anyone wants a copy of the FBI's "Recommendations and Guidelines for Using Closed-Circuit Television Security Systems in Commercial Institutions" just say the word.

Regarding Johnson's Criteria, I believe that these should only be used in conjunction with night vision (thermal) cameras and they describe the ability to, for example, tell the difference between enemy or friend - thus, these criteria creditor only for military use!

Ok John, thanks, I saw that it was now as web text, but I had the "original" as a pdf. Looks, however, that the content is the same.
I agree - these recommendations have significant shortcomings today. But as I mentioned, it's probably the case that many of the "new" recommendations today are sometimes a mix of these recommendations and other (maby European) Standards.

What is the definition of "Classification"? The same as "Recognition"?