Shaving digitally

Have you ever browsed old photographs only to have wondered how much better you could have looked had that bushy beard not been hiding your face at the time? Or are you contemplating shaving your beard of many years but you would like to see the final result before the event just in case? It is now possible to satisfy you curiosity using a new image-based shaving technique developed at CMU's Robotics Institute.

Virtual shaving is achieved by modeling human faces in images as a set of layers that can be separated and manipulated at will; in fact, the method is not only good for shaving but also for adding a beard or even transferring a beard from one photo to another. If you find that you are losing your hair, you could potentially use this method to virtually enhance your photograph with a full set of luscious hair.

The CMU researchers utilized a machine learning method to predict what a person's face looks like under a beard making it possible to reconstruct features not visible in the original image. Using a large database of faces with and without beards (properly labeled for supervised learning,) the researchers learned two subspaces (one for each class of faces) and a model of the differences between the two subspaces. These are later used to transform a bearded face image to a non-bearded one and vice versa. Below is an example beard removal from the published paper.

The result shown above was obtained after training with a small number of images; the total number of images used was about 1200, i.e., a very small number for machine learning to be the most effective. As the authors proposed in their Eurographics 2008 paper, a larger set of images available for training should provide a large improvement on the final result. Finally, the same method is general enough to be used for other digital image manipulation tasks such as removing one's glasses.