Almost all human faces have common characteristics, such as two eyes and one mouth. Still, some people, affected by face blindness, cannot recognize one face from another one. So it’s understandable that face recognition is a major challenge for computer vision systems.

In “Facing facts in computer recognition,”, the Pittsburgh Post-Gazette reports that a team from Carnegie Mellon University’s Robotics Institute has developed a very accurate software to find faces within images. By analyzing only 768 pixels, the system can detect 93 percent of the faces in a set of images while falsely identifying four objects as faces.



The Face Detector Demo is available online and you can submit an image for analysis and receive the results by e-mail. The technology will be used for security purposes, but also by digital photography companies who want to automatically reduce “red eye” effects.

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