October 25,2008:
The proliferation of video cameras
on the battlefield (in UAVs, ground robots and for base security) has provided
a huge library of images that show bad guys doing what bad guys do. This can
range from moving around carrying weapons, to using those weapons, to the
particular driving patterns of people up to no good. This is a unique resource,
and the U.S. Department of Defense is putting together a library of these
images. This is similar to older still pictures libraries, which were
eventually used by pattern recognition software to let machines examine the
millions of images digital photo satellites began producing decades ago. The
basic problem was that there were quickly too many pictures for human analysts
to examine. Computers had to do much of the work, or else most of the images
would go unexamined. This technology was quickly adapted to the kind of combat
encountered in Iraq and Afghanistan, and terrorist operations in general.
Now we have
all those cameras producing millions of hours of video a year, which has to be
examined by humans, to find whatever useful may be there. While this video is
usually examined, on-the-spot, by UAV sensor operators, or security troops
guarding bases, a lot of it has more to reveal. The people first viewing don't
always detect everything useful.
Research has
shown that people staring at live video feeds start losing their ability to
concentrate on the images after about twenty minutes. This problem has been
known for some time, and the military (not to mention civilian security firms)
have been seeking a technological solution. It's actually not as bad with UAVs,
because the picture constantly changes, but cameras that are fixed can wear
operators out real quick.
The basic
tech solution is pattern analysis. Since the most common video is digital, it's
possible to translate the video into numbers, and then analyze those numbers.
Government security organizations have been doing this for some time, but after
the fact. It's one thing to have a bunch of computers analyze satellite photos
for a week, to see if there was anything useful there. It's quite another
matter to do it in real time. But computers have gotten faster, cheaper and
smaller in the last few years, and programmers have kept coming up with more
efficient routines for analyzing the digital images. Commercial firms already
have software on the market that will analyze, in real time, video, and alert a
human operator if someone, or something (you are looking for) appears to be
there.
While some
military analysis does not have to be real time (like the system used in Iraq
to compare today's and yesterdays photos of a road to see if a bomb may have
been planted), the most common need is for real time analysis. Several times a
year now, a new software package shows up that does that, or tries to. These
systems are getting better. Many can definitely beat your average human
observer over time (several hours of viewing video). The real time analysis
software is rapidly evolving. You don't hear much about it, because if the
enemy knows the details of how it works, they can develop moves that will
deceive it (or, to be more accurate, make the pattern analysis less accurate.)
Already, this software is being used as an adjunct to human observers, and
gradually taking over. There will always be a human in the loop, to confirm
what the software believes it has found.
Another area
of active research is night vision goggles that think. This will be achieved by
sufficiently miniaturizing the computer power needed. This will first be seen
with heat imaging devices, commonly used by armored vehicles, combat robots and
weapons sights, with this kind of software. Troops equipped with this equipment
won't be immune to night attack, but the attackers will have to move as if it
was daylight, slowly and from behind whatever cover is available. Moving
swiftly under cover of night will no longer be possible if the other side has
night vision devices equipped with pattern recognition software.
But the big
breakthrough, which may already have been achieved, is a predictive analysis
system that can quickly examine thousands of hours of video from a specific
area, and calculate the probability that certain vehicles, or individuals, down
there, are up to no good. This works if you have lots of examples of people you
know are up to no good. The predictive analysis looks for enough indicators to
make it likely that something bad is going down. When done in real time, the
analysis software can instantly alert that something bad is about to happen at
a specific location. If nothing does happen, that is saved and added to the
library of experience the analysis software uses to make predictions. In effect,
the predictive analysis software gets smarter the more often it is used. And
the library of combat zone video images grows larger as well, making it
possible for the analysis software to sniff more behavior patterns that predict
bad actions.