Abstracted painterly renderings using eye-tracking data
Anthony Santella, Doug DeCarlo · 2002
When used by artists, manual interfaces for painterly rendering can yield very satisfying abstract transformations of images. Automatic techniques produce interesting paintings as well, but can only recast pictures in a different style without performing any abstraction. At best, information is removed uniformly across the image, without emphasizing the important content. We describe a new approach for the creation of painterly renderings that draws on a model of human perception and is driven by eye-tracking data. This approach can perform meaningful abstraction using this data, with the minimum interaction possible: the user need only look at the image for several seconds. We demonstrate the effectiveness of this interactive technique and compare it with a fully automatic approach.