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Here's the scenario: You pass a person on the sidewalk wearing a
pair of stylish shoes. The leather is light brown, with a rounded toe
and a buckle. You'd like to find a similar pair for yourself online.
But searching for "shoes, light brown, rounded toe, buckle" probably
won't get you very far.
Launched today, Like.com offers
a new method of searching--using pictures instead of text--that may
provide a better way to shop. The visual search engine uses a picture
as a starting point, and it crawls the webpages of more than 200 online
stores, including Amazon.com and L.L. Bean, searching for pictures of
items similar to the one you're interested in. Currently, Like.com
looks at more than two million different items in four categories:
shoes, handbags, watches, and jewelry. In the next few months, the
company hopes to add shirts, pants, and dresses.
"We
realized that the place visual search could add the most value is the
place where it's hard to describe an item with words--where you'd want
to submit a photo rather than enter text," says Munjal Shah, creator of
Like.com. Shah is also the CEO of the photo-sharing website Riya.com, a
site that recognizes faces in submitted photos (see "Face Recognition Software Goes Public").
Like.com
works by using an image as a springboard for the search. Users can base
their search on photos from 200 online retailers, and they can select
accessories from celebrity photos in the Like.com database. Users can
also indicate which characteristics, such as color, shape, or pattern,
are most important to them. In addition, they can use traditional text
filters to sort by brand, style, and price.
Special
software developed by Like.com's team of computer scientists recognizes
similar objects by deconstructing pictures of them. Each image is
broken down into 10,000 numbers that represent more than 30 features of
the item--for example, the full spectrum of colors that appear in a
handbag, its lumps and curves, and the glossiness of its exterior.
Additionally, a user can highlight a particular feature of the item
that he or she likes the most--for instance, the strap of the watch or
the shape of its face--and search within that constraint. The 10,000
numbers that describe the original picture are compared with the
numbers that describe the pictures on merchants' websites.
Developing
the visual search system was tricky, says Shah. He and his team had to
spend a lot of time making sure that their crawler could access the
high-resolution version of an image on merchants' sites (fewer pixels
don't provide as much useful information to compare). And, if a
merchant's website offered multiple views and colors, the Web crawler
needed to be able to access those as well. Like.com works best with
watches and handbags, says Shah, simply because they tend to photograph
consistently and there is little glare. Jewelry is more challenging for
the search engine to match due to the variation in
the way shiny gold and glistening diamonds are lit in photos.
By Kate Greene
Read article at techreview.com