Principal-channels for One-sided Object Cutout

We introduce principal-channels for cutting out objects from an image by one-sided scribbles. We demonstrate that few scribbles, all from within the object of interest, are sufficient to mark it out. One-sided scribbles provide significantly less information than two-sided ones. Thus, it is required to maximize the use of image-information. Our approach is to first analyze the image with a large filter bank and generate a high-dimensional feature space. We then extract a set of principal-channels that discern one object from another. We show that by applying an iterative graph-cut optimization over the principal-channels, we can cut out the object of interest.