Now there’s no escape from CCTV… Researchers reveal software that can track people as they walk from camera to camera in real time – and say it could have tracked the Boston bombers ‘within hours’

image

Firm says technology could
allow for ‘real time Google
Earth’ with live people
shown
Researchers say system
could have tracked Boston
bombers ‘within hours’
Could also allow people to
be tracked without having to
sift through hours of
footage
We are all used to our image being
captured by CCTV everywhere we
go – but now, it is about to get a
lot smarter.
Researchers have unveiled smart
software that can automatically
track people across moving and
still cameras – allowing them to be
automatically tracked in real time.
The cameras can first identify a
person in a video frame, then
follow that same person across
multiple camera views – and can
even analyse live footage from
drones.
Scroll down for video

The University of Washington
researchers are developing the
software to work in real time,
which could help pick out people
crossing in busy intersections, or
track a specific person who is
dodging the police.

HOW IT COULD BE USED

The researchers say the system
could create a ‘super GPS’.
‘Imagine a typical GPS display that
maps the streets, buildings and
signs in a neighborhood as your
car moves forward, then add
humans to the picture,’ they say.
‘With the new technology, a car
with a mounted camera could take
video of the scene, then identify
and track humans and overlay
them into the virtual 3-D map on
your GPS screen.’

The University of Washington
electrical engineers say their
system could save hours of sifting
through CCTV footage – and even
revolutionise GPS systems.

The UW researchers are developing
the software to work in real time,
which could help pick out people
crossing in busy intersections, or
track a specific person who is
dodging the police.

‘Tracking humans automatically
across cameras in a three-
dimensional space is new,’ said
lead researcher Jenq-Neng Hwang,
a UW professor of electrical
engineering.
‘As the cameras talk to each other,
we are able to describe the real
world in a more dynamic sense.’
Hwang and his research team
presented their results last month
in Qingdao, China, at the
Intelligent Transportation Systems
Conference sponsored by the
Institute of Electrical and
Electronics Engineers, or IEEE.
He says the system would have
been able to analyse footage from
the Boston combing and track
suspect’s movements across
cameras within hours of the
explosion taking place.
‘Our idea is to enable the dynamic
visualization of the realistic
situation of humans walking on the
road and sidewalks, so eventually
people can see the animated
version of the real-time dynamics
of city streets on a platform like
Google Earth,’ Hwang said.
Hwang’s research team in the past
decade has developed a way for
video cameras – from the most
basic models to high-end devices –
to talk to each other as they record
different places in a common
location.
The problem with tracking a
human across cameras of non-
overlapping fields of view is that a
person’s appearance can vary
dramatically in each video because
of different perspectives, angles
and color hues produced by
different cameras.

The researchers overcame this by
building a link between the
cameras.
Cameras first record for a couple of
minutes to gather training data,
systematically calculating the
differences in color, texture and
angle between a pair of cameras
for a number of people who walk
into the frames in a fully
unsupervised manner without
human intervention.

After this calibration period, an
algorithm automatically applies
those differences between cameras
and can pick out the same people
across multiple frames, effectively
tracking them without needing to
see their faces.
The research team has tested the
ability of static and moving
cameras to detect and track
pedestrians on the UW campus in
multiple scenarios.
In one experiment, graduate
students mounted cameras in their
cars to gather data, then applied
the algorithms to successfully pick
out humans and follow them in a
three-dimensional space.

They also installed the tracking
system on cameras placed inside a
robot and a flying drone, allowing
the robot and drone to follow a
person, even when the instruments
came across obstacles that blocked
the person from view.
The linking technology can be used
anywhere, as long as the cameras
can talk over a wireless network
and upload data to the cloud.
Inevitably, people will have privacy
concerns, Hwang said, and the
information extracted from cameras
could be encrypted before it’s sent
to the cloud.
‘Cameras and recording won’t go
away.

HOW IT WORKS

Cameras first record for a couple of
minutes to gather training data,
systematically calculating the
differences in color, texture and
angle between a pair of cameras
for a number of people who walk
into the frames in a fully
unsupervised manner without
human intervention.
After this calibration period, an
algorithm automatically applies
those differences between cameras
and can pick out the same people
across multiple frames, effectively
tracking them without needing to
see their faces.
The research team has tested the
ability of static and moving
cameras to detect and track
pedestrians on the UW campus in
multiple scenarios.
In one experiment, graduate
students mounted cameras in their
cars to gather data, then applied
the algorithms to successfully pick
out humans and follow them in a
three-dimensional space.
They also installed the tracking
system on cameras placed inside a
robot and a flying drone, allowing
the robot and drone to follow a
person, even when the instruments
came across obstacles that blocked
the person from view.

‘We might as well take advantage
of that fact and extract more useful
information for the benefit of the
community,’ he added.
This detailed visual record could
be useful for security and
surveillance, monitoring for
unusual behavior or tracking a
moving suspect. But it also tells
store owners and business
proprietors useful information and
statistics about consumers’ moving
patterns.

A store owner could, for example,
use a tracking system to watch a
shopper’s movements in the store,
taking note of her interests. Then,
a coupon or deal for a particular
product could be displayed on a
nearby screen or pushed to the
shopper’s phone – in an instant.
Leveraging the visual data
produced by our physical actions
and movements might, in fact,
become the next way in which we
receive marketing, advertisements
and even helpful tools for our
everyday lives.

The University of Washington
researchers are developing the
software to work in real time,
which could help pick out people
crossing in busy intersections, or
track a specific person who is
dodging the police.

The research team has tested the
ability of static and moving
cameras to detect and track
pedestrians on the UW campus in
multiple scenarios, even using
cars and drones.

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