Image Appearance Exploration by Model-Based Navigation

Lior Shapira, Ariel Shamir, and Daniel Cohen-Or


Changing the appearance of an image can be a complex and non-intuitive task.

Many times the target image colors and look are only known vaguely and many

trials are needed to reach the desired results. Moreover, the effect of a

specific change on an image is difficult to envision, since one must take into

account spatial image considerations along with the color constraints. Tools

provided today by image processing applications can become highly technical and

non-intuitive including various gauges and knobs.

In this paper we introduce a method for changing image appearance by

navigation, focusing on recoloring images. The user visually navigates a high

dimensional space of possible color manipulations of an image. He can either

explore in it for inspiration or refine his choices by navigating into sub

regions of this space to a specific goal. This navigation is enabled by

modeling the chroma channels of an image's colors using a Gaussian Mixture

Model (GMM). The Gaussians model both color and spatial image coordinates, and

provide a high dimensional parameterization space of a rich variety of color

manipulations. The user's actions are translated into transformations of the

parameters of the model, which recolor the image. This approach provides both

inspiration and intuitive navigation in the complex space of image color



Publication typeArticle
Published inComputer Graphics Forum
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