Arun Vemury: Most people going through
these security checkpoints proceed by themselves. But about 40% of people travel
with friends or family. So the intent here is how do we help make sure that this stuff
works, the way people actually travel. Dave: Welcome to Tech Speak, a mini episode of
the Technologically Speaking Podcast. I'm Dave, sound editor for S&T. In September, our
podcast team attended the 2022 Biometric Technology Rally at our Maryland Test
Facility in Upper Marlboro, Maryla
nd, and they had a great time seeing several facial
recognition technologies up close and personal. At the start of this mini episode, you heard
repeat guest, Arun Vemury, Director of S&T's, Biometric and Identity Technology Center, speak
briefly about the challenges being addressed by this year's Tech Rally. Now let's hear Arun
talk about what exactly a Tech Rally is. Arun Vemury: Today is the first day
of the DHS S&T Biometric Technology Rally for 2022. We're actually putting
together an
industry challenge where we, give a challenging scenario to industry. We
tell them how we want the technology to perform, and we let them go at it. We give them a hard
problem and we let them innovate and come up with creative solutions to solve a hard problem.
And today, the use case we're going after is this thing called high throughput, where we
have a large number of people who we need to have their identity verified before they go into
let's say secure or a sterile area. In general, w
e're trying to do things where people
are screened in less than three seconds per person. Ideally it should be under six
seconds per person, but really we're pushing for that three-second mark. And really what we're
trying to do is also just give industry room to innovate. We give them a volume and they can put
whatever set of technologies they want in there. Arun Vemury: And the intention is
as people walk and enter that space, their biometrics are collected and their identity is verified
before they leave. And all
of this happens in under three seconds. Dave: This was the fifth annual
Biometric Technology Rally for S&T. Each one aims to address new
and emerging challenges in identity verification. Here Arun describes
the focus of this year's event. Arun Vemury: For the last couple of years, our
rallies have been focused on this high throughput use case where we are trying to get people
through the process as quickly as possible, make it as easy and intuitive
to use as pos
sible. However, in the past it's always been one person at
a time. the challenge there is that's great. And most travelers or most people going
through these security checkpoints proceed by themselves. But about 40% of people travel
with friends or family. So, the intent here is how do we help make sure that this stuff works
the way people actually travel and they move. Arun Vemury: So, the challenge here that's used,
that's new and different, as there were processing groups of people, smal
l groups of people. So the
industry participants who are working on the rally don't know if they're going to see one person or
12 people. But every time a group comes through, they're supposed to figure out how many people
are in the group. Take good photos of each one of those people and send the best possible
photo back to our matching systems. It's not trivial to figure out how many people are
in the group, which face is the best face, and make sure you're sending the best image
back to
the biometric system to try to get a good matching. So, we're trying out a lot of new
things here that are relatively unique. It'll be interesting to see how industry kind of rises
to the occasion. And that'll help us figure out maybe is this something that might be, really
operationally viable two or three years from now? Arun Vemury: Or is this something that might
require five or six years? Something that might take a little bit more time. This helps DHS
stakeholders understand what the
state of the art of the technology really is, so that they can make
better choices and plan because that might help them figure out what use cases make sense, what
use cases don't make sense. So with this rally, you know, we are looking at a couple of new
things. So, one is this whole idea of the privacy measurement as part of the Rally. How
do we make sure that we're collecting images of people who are walking into a space and they're
specifically opting in, but we're also respecting the
privacy of people who specifically opt out.
And they might be processed right next to people who opt in. These cameras have wide fields
of view, you know, they have a wide screen. Arun Vemury: How do we make sure that we're
only collecting the faces of some people, but not other people? So, we're trying to make
sure that the systems are actually designed for that purpose with privacy built in. Another
thing is this whole idea of group processing, being able to process a whole group
of peop
le. Maybe some are taller, maybe some are shorter. You might have tall
people in front of short people. How do the systems accommodate the way people move
together and travel? And then finally, as always, we focus a lot on the questions of
equitability and fairness. Do the technologies really accommodate the diversity of people who
are using them for things based off of gender, skin tone, race, ethnicity? We wanna make
sure the technologies work for everyone. Dave: During the event, our pod
cast
team had the rare opportunity to test the facial recognition technology and see it in
action with their very own eyes. Let's listen as Arun gives our team a demonstration of the
technology and walks them through how it works. Arun Vemury: During the Rally, one of the things
we do is we do basically side by side testing where each company has their own designated
space, and we have volunteers interact with each one of the systems, and we evaluate how
well the systems work with those vo
lunteers. Does it take photos of everyone who it's supposed
to take a photo of? Does it not take photos of people who've opted out and walked around the
system? When it fails or when there are errors, are they attributable to people who
have like maybe certain demographic characteristics or something else? Why? Why do the
technologies work sometimes and not work others? Arun Vemury: And the intention here is really
to make technologies that don't have errors. We want this stuff to work to b
e easy to use and
be incredibly intuitive for the normal traveling public to interact with. So, in each one of these
systems, we have a different system mostly from different companies. In some cases, we have
two submissions from one company. But it's really about trying out different technologies,
different configurations, and see which ones work and which ones, maybe needs some additional
refinement. This system looks like it has a user interface where it's got a screen above it where
it
's welcoming people to come through. It's also attracting attention so that as people look at
that, there's also a camera nearby so that you get a nice posed face. As you walk through, it's
figuring out how many people are in the field of view. Are you opting into the system? Are you
in the area where you're definitely gonna walk through? Or are you in this area around the system
where you're not supposed to walk through? So, you see on that screen, like on the bottom
left-hand corner, you
see those blue curtains. Arun Vemury: If you're in the blue curtain, it's
not supposed to take your photo. And if you're not close enough, it's not supposed to take your
photo. That's the whole point is it's not gonna take your photo. You're not close enough. But as
you get closer, and I'm taking steps forward here closer and closer to the point where it's within
the specific range in this case, maybe within four or five feet, that it'll actually locate
my face and finally actually take my
photo. Arun Vemury: And the other thing too, so in that
case, you just saw that my, it took my photo as soon as I crossed that line, but it didn't take
my photo before then. And if I walked over here to the side and I was going through an opt out
process and I don't like facial recognition, I don't want it taking my face. I can come over here
and as I turn that corner and come around here, I'm in that blue curtain area, so it's not gonna
take my photo. But the theory here is we want people
who opt in to go through and basically not
have to do much to not have a lot of interaction, follow a lot of instructions because most people
are busy and they're just trying to complete their day. So here, if I walk through, I'm not really
doing anything in particular. It still collects my photo and it works and it takes that really
nice photo and sends it back to the matcher. Dave: This technology is so innovative. I wish
I had the opportunity to test it myself. Maybe next year. But for n
ow, hearing from Arun twice
now has definitely changed my perspective on airport screenings. You can learn more about
S&T's work with facial recognition technology by checking out season one, episode four of
Technologically Speaking, the Three-legged Stool. Thanks for listening, and be sure to
follow us at DHS SCITECH DHS, S C T E C H. Bye.
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