Directional Texture Transfer

by CGLab posted May 01, 2014
Extra Form
Author Hochang Lee,Sanghyun Seo,Seungtaek Ryoo,Kyunghyun Yoon
Location NPAR'10
Abstract A texture transfer algorithm modifies the target image replacing the high frequency information with the example source image. Previ- ous texture transfer techniques normally use such factors as color distance and standard deviation for selecting the best texture from the candidate sets. These factors are useful for expressing a texture effect of the example source in the target image, but are less than optimal for considering the object shape of the target image. In this paper, we propose a novel texture transfer algorithm to ex- press the directional effect based on the flow of the target image. For this, we use a directional factor that considers the gradient di- rection of the target image. We add an additional energy term that respects the image gradient to the previous fast texture transfer al- gorithm. Additionally, we propose a method for estimating the di- rectional factor weight value from the target image. We have tested our algorithm with various target images. Our algorithm can ex- press a result image with the feature of the example source texture and the flow of the target image.
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Directional Texture Transfer

Hochang Lee       Sanghyun Seo       Seungtaek Ryoo       Kyunghyun Yoon

CAU CGLab


DTT_BIG.JPG

Abstract

A texture transfer algorithm modifies the target image replacing the high frequency information with the example source image. Previ- ous texture transfer techniques normally use such factors as color distance and standard deviation for selecting the best texture from the candidate sets. These factors are useful for expressing a texture effect of the example source in the target image, but are less than optimal for considering the object shape of the target image. In this paper, we propose a novel texture transfer algorithm to ex- press the directional effect based on the flow of the target image. For this, we use a directional factor that considers the gradient di- rection of the target image. We add an additional energy term that respects the image gradient to the previous fast texture transfer al- gorithm. Additionally, we propose a method for estimating the di- rectional factor weight value from the target image. We have tested our algorithm with various target images. Our algorithm can ex- press a result image with the feature of the example source texture and the flow of the target image.