Visual dictionary

[David Morris]

http://people.csail.mit.edu/torralba/tinyimages/


We present a visualization of all the nouns in the English language
arranged by semantic meaning. Each of the tiles in the mosaic is an
arithmetic average of images relating to one of 53,463 nouns. The
images for each word were obtained using Google's Image Search and
other engines. A total of 7,527,697 images were used, each tile being
the average of 140 images. The average reveals the dominant visual
characteristics of each word. For some, the average turns out to be a
recognizable image; for others the average is a colored blob. The list
of nouns was obtained from Wordnet, a database compiled by
lexicographers which records the semantic relationship between words.
Using this database, we extract a tree-structured semantic hierarchy
which we use to arrange tiles within the poster. We tessellate the
poster using the hierarchy so that the proximity of two tiles is given
by their semantic distance. Thus the poster explores the relationship
between visual and semantic similarity. For a large part of our
language the two are closely correlated as shown by the extent of
visual clustering within the poster. The large-scale groupings
correspond to broad categories such as plants or people. Within the
plant cluster, for example, tighter semantic groupings are visible
such as flowers or trees. In turn each of these clusters contains
further groupings all the way down to individual, highly specific
nouns. The averaging within each tile removes the variation between
images of a given word, enhancing the similarly between neighbors. By
clicking on top of the map, you will see the word corresponding to
that location, the average image and the first 16 images returned by
the image search online tools.