Face Recognition

Recognition may be viewed as a sub-problem of discrimination and/or classification. Many technical solutions to recognition problems depend on proprietary set of feature vectors that collectively help discriminate one sample from another. There are many examples of recognition technologies in use today. Examples include biometrics and other applications involving voice (or speech), image, scene, gesture, smell, and/or video.

Remember the Bronstien twins who cracked the 3D-facial recognition problem in 2003. They developed routines that could classify themselves apart successfully. A recent experimental example of this comes from MyHeritage that takes your picture to match up with look-alike celebrities. A similar application called HNeT from AND Corporation tracks and recognizes up to four individuals simultaneously in real-time. It can recognize a face even when an individual ages. Another company is Identix provides face recognition software that can spot an individual in a crowd. Yet another example comes from Riya intended for photo sharing and searching. It can spot an individual from a given set of photos.

Searching (Google), Copying (Xerox), Classification (Yahoo), Summarization, Conversion, Assimilation, and Distribution have wide range of applications that support many businesses today. So, what do you think?