Carnegie Mellon University researchers have taken a first step toward this capability in study where they analyzed five million such images. (Agencies)
Researchers Eric Xing and Gunhee Kim looked at images associated with 48 brands in four categories: sports, luxury, beer and fast food. The images were obtained through popular photo sharing sites such as Pinterest and Flickr.
Their automated process unsurprisingly produced clusters of photos that are typical of certain brands. But some of the highly ranked associations underscored the type of information particularly associated with images and especially with images from social media sites.
Kim noted, are events where people tend to take and share lots of photos, each of which is an opportunity to show brands in the context in which they are used and experienced.
Marketers are always trying to get inside the head of customers to find out what a brand name causes them to think or feel."Now, the question is whether we can leverage the billions of online photos that people have uploaded," said Kim.
Digital cameras and smartphones have made it easy for people to snap and share photos from their daily lives, many of which relate in some way to one brand or another.
"Our work is the first attempt to perform such photo-based association analysis," Kim said. We cannot completely replace text-based analysis, but already we have shown this method can provide information that complements existing brand associations," said Kim.
Kim and Xing obtained photos that people had shared and had tagged with one of 48 brand names. They developed a method for analyzing the overall appearance of the photos and clustering similar appearing images together, providing core visual concepts associated with each brand.
They also developed an algorithm that would then isolate the portion of the image associated with the brand.
Carnegie Mellon University researchers have taken a first step toward this capability in study where they analyzed five million such images.