Hallucinating Faces - Robotics Institute Carnegie Mellon University
Hallucinating Faces

We have developed an algorithm that can be used to learn a prior on the spatial distribution of the image gradient for frontal images of faces. We have shown how such a prior can be incorporated into a super-resolution algorithm to yield 4-8 fold improvements in resolution (16-64 times as many pixels) using as few as 2-3 images. The additional pixels are, in effect, hallucinated. An example of the results of our algorithm is shown below:

Displaying 6 Publications

current staff

past head

  • Simon Baker

past contact

  • Simon Baker