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Comment by jhonovich | Hacker News Reader

I am the author of the referenced article. The problem is matching surveillance camera images (like from Lord & Taylor's) is impossible because of the steep down tilt angle of the cameras plus their low resolution. Smartphone images could be a little better as the angle is more head on and the resolution is higher. However, even those images tended to be in a wide field of view which means low pixel density, hurting matching performance. Last, but not least, the caps and sunglasses hurt recognition as well.

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Matching surveillance camera images is always possible no matter how bad the image quality is. The only matter is how many false positives show up.

Facial recognition algorithms always give their best matching candidates, with thresholds to skip those not quite matching ones. Your article makes it sound like no such results were produced at all, which is unlikely how recognition is supposed to work.

First of all, almost any facial surveillance system would simply reject images like those from Lord & Taylor's. The pixel density is simply too low to even attempt plus the downtilt would also likely trigger a rejection. That's how facial recognition does work in practice.

Even if the system would allow it, not only would false positives be enormous, you'd probably miss the match as well (false negative).

Not impossible though. Given that such software is used to steer the future efforts of the investigators, it is possible that the software does say "no match found" if the probability of a real match is too low.

Why is surveillance video not HD? Shouldn't this quality be almost a commodity by now? How different are these cameras than what you get in, say the latest Samsung Galaxy S4, for example:

http://en.wikipedia.org/wiki/Samsung_Galaxy_S4

Probably because the cost of surveillance cameras is more than just the cost of the resolution or storage. the ones that hang outside need to be weather proof and vandalism proof. they were probably bought as part of a large and expensive system, intended to be paid off over 10-15 years[0], to replace all those cameras whenever more resolution becomes available, is probably quite expensive, regardless of how cheap the actual camera is. It's a lot of cameras, in a lot of hard-to-reach places, with expensive reinforced casings, and would the output format of the cameras be compatible with the old system?

OTOH, I do actually see more and more HD (or relatively high def) surveillance footage. It all depends on how when the security system was installed, I guess. Also smaller businesses can afford a shorter turnaround for these things, as well as not having the handicap of a head-start[1].

[0] actually I'm guessing those lifetime spans, it seems a bit much? but I also can't see anyone signing off on a security system that's expected to be replaced in 5 years. good thing my job isn't facility management ... :P

[1] http://en.wikipedia.org/wiki/Law_of_the_handicap_of_a_head_s... , how odd, is there no common English phrase for this law?

In business terminology, a common English phrase would be "first-mover disadvantage".

Its not only about the cameras. Its currently expensive to store all that HD video. ( and now, one cant just upload it to the cloud. Necessary bandwidth isn't yet available locally ).

One are also dealing with a lot of legacy systems her. But the next generation surveillance system will probably be HD, and then maybe 3D, 4k, 16k etc.

Surveillance cameras are typically bought and then forgotten. So the new ones are probably HD, but you get a collection of cameras between HD and Betamax if you look at the cameras that are actually in use.

And for outdoor cameras, how often do the lenses get cleaned? I'd think that in a city center, with lots of car exhaust, etc. they'd be pretty dusty/greasy in just a few months. HD won't help much if there's a film of diesel exhaust soot on the lens.

with so many distributed cameras, why not use them to make a composite, hi-def image, like we do with radio telescopes?

Interesting to see articles promoting adding more surveillance cameras for all their flaws (bad angle, resolution trails behind phone cameras, etc). I would focus on acquiring publicly available photo data in real time at dense events and scan them. I.e. crowdsourced surveillance. I'm sure someone is working on that.

Thank you for the article.

In a real life scenario, surveillance camera images are all you will get to work with, most likely. So maybe, the focus should be on figuring a way out to recognize individuals based on images taken at those angles. Is there any progress in this regard?

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