TECHNOLOGY:
NS040410
 #30  Lost? Send snap and SOS to...: Photo recognition software
          can tell you precisely where you are and how to get to
          your destination

 James Randerson

YOU are lost in a foreign city, you don't speak the language and
you are late for your meeting. What do you do? Take out your
cellphone, photograph the nearest building and press send. For a
small fee, photo recognition software on a remote server works
out precisely where you are, and sends back directions that will
get you to your destination. That, at least, is what two
researchers at the University of Cambridge hope their software
will one day be used for.

Roberto Cipolla and Duncan Robertson have developed a program that
can match a photograph of a building to a database of images. The
database contains a three-dimensional representation of the
real-life street, so the software can work out where the user is
standing to within 1 metre. This is far better than existing
systems can manage. GPS satellite positioning is accurate to 10
metres at best, and can be useless in cities where tall buildings
shield the user from direct line of sight with the satellites.
And positioning using cellphone base stations has a precision of
between 50 and 100 metres. 'Telling people 'You are in the
vicinity of X,' is no good to man nor beast,' says John Craig of
Cambridge Positioning Systems, a company that develops software
for locating mobile phones.

Unlike the GPS or cellphone base station approaches, Cipolla and
Robertson's software can tell which direction you are facing. So
the service can launch straight into a set of directions such as
'turn to your left and start walking', or give information on the
building in the photograph.

When their system receives an image it begins by identifying
vertical and horizontal lines. Next, it warps the image so that
the horizontals are all parallel with each other, and the same
for verticals. This transforms the picture into one that was
taken square on, rather than at an angle. The software then looks
for useful features, such as the corners of windows and doors,
and extracts the colours and intensities of the pixels around
them. Next, it searches the image database for matching data,
using the base station the cellphone's signal came from as a
guide. Finally, it uses the differences between the two images to
calculate the photographer's position.

The software can match two images even when they are taken at a
different times of day, from different angles and with clutter
such as pedestrians and vehicles in the way. 'That's an easy
problem for a human, but it's very difficult for a computer,'
says Robertson .

However, the system's commercial future is uncertain. 'The
question is: how much are people prepared to pay for it, and how
often will they use it?' says Rob Morland, of technology
consultants Scientific Generics near Cambridge. 'That's a tough
one.' For now, Cipolla and Robertson are optimistic. Last month
they received funding to start working on a prototype to cover
all the buildings in Cambridge city centre.
Snap happy
James Randerson
With my digital camera slung round my neck, I could easily be
mistaken for another tourist enjoying an English spring afternoon
in Cambridge. But while the day trippers will be filling their
albums with shots of King's College chapel or the Mathematical
Bridge, I am after more modest game: the shops surrounding Market
Square.

Though my snaps won't net me a Pulitzer Prize, they do have a
serious purpose. I wanted to put Roberto Cipolla and Duncan
Robertson's software through its paces and find if it works.

Back in the lab, my photos look very different from those in the
database. The buildings are taken from an oblique angle rather
than front-on, shop displays are unrecognisable, and I've made
sure there are plenty of cars and people in the foreground to
throw the program off-track.

Unsporting I admit, but real-life users will not care about making
things easy; they will just want to know where they are. Despite
my efforts, the software was only confused by the most fiendish
of my eight snaps, which had a truck blocking around a third of
the building.

In Robertson's more systematic test, he tried to match 100 photos
to a database of the same size. In the three cases where the
software fell down, it had either confused two identical
buildings or two similar parts of the same building. Updated
software could spot this error because the program gives such
database images a high similarity score. This could be used as a
trigger to prompt the user to take a snap of another building,
say, to confirm the fix.



____________________________________________________________
Copyright 2004 Reed Business Information US, a division of Reed Elsevier
Inc.
 


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