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The Most Advanced Face Detection Algorithm Yet

By   /  February 17, 2015  /  No Comments

285/365 Faces of the Boardroomby Angela Guess

The MIT Technology Review reports, “Back in 2001, two computer scientists, Paul Viola and Michael Jones, triggered a revolution in the field of computer face detection. After years of stagnation, these guys’ breakthrough was an algorithm that could spot faces in an image in real time. Indeed, the so-called Viola-Jones algorithm was so fast and simple that it was soon built into standard point and shoot cameras. Part of their trick was to ignore the much more difficult problem of face recognition and concentrate only on detection. They also focused only on faces viewed from the front, ignoring any seen from an angle. Given these bounds, they realised that the bridge of the nose usually formed a vertical line that was brighter than the eye sockets nearby. They also noticed that the eyes were often in shadow and so formed a darker horizontal band.”

The article continues, “So Viola and Jones built an algorithm that looks first for vertical bright bands in an image that might be noses, it then looks for horizontal dark bands that might be eyes, it then looks for other general patterns associated with faces. Detected by themselves, none of these features are strongly suggestive of a face. But when they are detected one after the other in a cascade, the result is a good indication of a face in the image. Hence the name of this process: a detector cascade. And since these tests are all simple to run, the resulting algorithm can work quickly in real-time. But while the Viola-Jones algorithm was something of a revelation for faces seen from the front, it cannot accurately spot faces from any other angle. And that severely limits how it can be used for face search engines.”

It adds, “Which is why Yahoo is interested in this problem. Today, Sachin Farfade and Mohammad Saberian at Yahoo Labs in California and Li-Jia Li at Stanford University nearby, reveal a new approach to the problem that can spot faces at an angle, even when partially occluded. They say their new approach is simpler than others and yet achieves state-of-the-art performance.”

Read more here.

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