Google image search gets a ’swirl’

November 19, 2009 · Filed Under News · Comment 

Google Labs on Tuesday brought more focus to finding pictures online, adding a “Swirl” tool that automatically groups similar images into categories presented on results pages.

Aparna Chennapragada, the Google product manager said, “What Image Swirl does is it really organizes automatically image search results into groups and sub-groups.”

“It’s not just the face, the color, the visual features of the images; we look inside the image and ask how they relate to each other on a pixel level, she added.

Swirl uses algorithms, metadata, and facial recognition software to distinguish between structures, places, people, and even time of day in digital images.

Online image search till date has resulted in results pages lined with thumbnail pictures that people sift through individually.

Yushi Jing, the Google software engineer who worked on image Swirl’s technology said, “As humans we can easily tell which images should be grouped together by looking at them.”

Users can experiment with Image Swirl at Google Labs and the gauged feedback will be utilized in improving the tool with the ultimate objective being to one day incorporate it in the California Internet giant’s public search engine.

Google image search gets a ’swirl’

November 17, 2009 · Filed Under News · Comment 

On Tuesday, Google Labs added the newly developed ‘Swirl’ tool to focus on finding more relevant pictures on the internet.

Swirl tool automatically groups similar images into categories presented on results pages.

Aparna Chennapragada, the Google product manager said, “What Image Swirl does is it really organizes automatically image search results into groups and sub-groups.”

He further added, “It’s not just the face, the color, the visual features of the images; we look inside the image and ask how they relate to each other on a pixel level.”

The new product from the internet search giant Google, Swirl, uses algorithms, metadata, and facial recognition software to distinguish between structures, places, people, and even time of day in digital images.

Online image search has traditionally delivered results pages lined with thumbnail pictures that people sift through individually.

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