With an average of 101,000 photos in each Facebook user’s social network, how many clicks would it take to caption every one? Face.com launches Photo Tagger, a program that harnesses the most advanced facial recognition technology to auto-tag photos in seconds. Previously a private alpha, Photo Tagger debuts to the public with an unprecedented Face Alerts system, which notifies users when photos of themselves or their friends are uploaded – even if they are not tagged.

The free application utilizes facial recognition technology to auto-tag photos, identifying millions of faces from billions of photos in mere seconds, and also provides users with unprecedented control over their online identities. The Face Alerts feature automatically and continuously scans newly uploaded (untagged and tagged) photos to notify users whenever her face (or a friend’s face) is found.

Face.com developed Photo Tagger as a tagging short-cut: in two clicks, Facebook users can quickly and efficiently tag all of the photos in an album, maximizing sharing capabilities. Once the user selects the album (either their own or a friends’), Photo Tagger utilizes facial recognition algorithms to scan the photos, batch subjects into groups and suggest tags. Confirmed tags are then pushed directly onto Facebook, mirroring its privacy settings, and the result is an album of meticulously tagged photos, despite varying lighting, quality, backgrounds, angles, focus and facial expressions.

“Home to billions of images, Facebook is not only the world’s largest social network but also the largest photo sharing site,” said Gil Hirsch, CEO, Face.com.

Recently published research, including an academic benchmark by the University of Massachusetts and studies from multiple major conferences jointly conducted with the Face.com team, consistently recognized Face.com algorithms as state-of-the-art, outperformed only by humans. With an emphasis on speed, social experience and control, Photo Tagger identifies faces where other face search programs, including Picasa, fall short.