Today there are more low-quality video cameras--surveillance and traffic cameras, cell-phone cameras and webcams--than ever before. But modern search engines can't identify objects very reliably in clear, static pictures, much less in grainy YouTube clips. A new software approach from researchers at Carnegie Mellon University could make it easier to identify a person's face in a low-resolution video. The researchers say that the software could be used to identify criminals or missing persons, or it could be integrated into next-generation video search engines.
Today's face-recognition systems actually work quite well, says Pablo Hennings-Yeomans, a researcher at Carnegie Mellon who developed the system--when, that is, researchers can control the lighting, angle of the face, and type of camera used. "The new science of face recognition is dealing with unconstrained environments," he says. "Our work, in particular, focuses on the problem of resolution."
Read more at - 'A Face-Finding Search Engine'