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By DAViD CRAnDALL AnD noAh snAVeLy
At a local scale, we can build detailed
three-dimensional models of a scene
by combining information from thousands of two-dimensional photographs taken by different people and
from different vantage points. One key
representation for many of these tasks
is a network: a graph linking photos by
visual similarity or other measures.
This article describes our work in
using online photo collections to reconstruct information about the world
and its inhabitants at both global and
local scales. This work has been driven by the dramatic growth of social
content-sharing Web sites, which have
created immense online collections of
user-generated visual data. Flickr.com
alone currently hosts more than six billion images taken by more than 40 million unique users,
11 while Facebook.
com has said it grows by nearly 250 million photos every day.
While users of these sites are primarily motivated by a desire to share
photos with family and friends, collectively they are generating vast repositories of online information about
the world and its people. Each of these
photos is a visual observation of what
a small part of the world looked like at
a particular point in time and space.
It is also a record of where a particular
person (the photographer) was at a moment in time and what he or she was
paying attention to.
In aggregate, and in combination
with nonvisual metadata available on
photo-sharing sites (including photo
timestamps, geotags, captions, user
profiles, and social contacts), these billions of photos present a rich source
of information about the state of the
world and the behavior of its people.
We can thus imagine extending the domain of computational photography to
encompass all of the world’s photos,
where the goal is to extract useful information about places and people from
our collective image data.
We have recently demonstrated how
to reconstruct information about the
world at both global and local scales
using collections such as those on
Understanding the world from
the sea of online photos.
CoMpUtatIonal photoGraphy often considers sets
of photos taken by a single user in a single setting, but
the popularity of online social media sites has created
a social aspect to photo collections as well. Photo-sharing sites such as Flickr and Facebook contain
vast amounts of latent information about our world
and human behavior. Our recent work has involved
building automatic algorithms that analyze large
collections of imagery in order to understand and
model people and places at a global scale. Geotagged
photographs can be used to identify the most
photographed places on Earth, as well as to infer the
names and visual representations of these places.