Improved Intuitive Appearance Editing based on Soft PCA

Abstract

During the last few years, many different techniques for measuring material appearance have arisen. These advances have allowed the creation of large public datasets, and new methods for editing BRDFs of captured appearance have been proposed. However, these methods lack intuitiveness and are hard to use for novice users. In order to overcome these limitations, Serrano et al. [SGM 16] recently proposed an intuitive space for editing captured appearance. They make use of a representation of the BRDF based on a combination of principal components (PCA) to reduce dimensionality, and then map these components to perceptual attributes. This PCA representation is biased towards specular materials and fails to represent very diffuse BRDFs, therefore producing unpleasant artifacts when editing. In this paper, we build on top of their work and propose to use two separate PCA bases for representing specular and diffuse BRDFs, and map each of these bases to the perceptual attributes. This allows us to avoid artifacts when editing towards diffuse BRDFs. We then propose a new method for effectively navigate between both bases while editing based on a new measurement of the specularity of measured materials. Finally, we integrate our proposed method in an intuitive BRDF editing framework and show how some of the limitations of the previous model have been overcomed with our representation. Moreover, our new measure of specularity can be used on any measured BRDF, as it is not limited only to MERL BRDFs [MPBM03].