Texture Transfer Based on Texture Descriptor Variations

Benoit Arbelot 1 Romain Vergne 1 Thomas Hurtut 2 Joëlle Thollot 1
1 MAVERICK - Models and Algorithms for Visualization and Rendering
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : In this report, we tackle the problem of image-space texture transfer which aims to modify an object or surface material by replacing its input texture by another reference texture. The main challenge of texture transfer is to successfully reproduce the reference texture patterns while preserving the input texture variations due to its environment such as illumination or shape variations. We propose to use a texture descriptor composed of local luminance and local gradients orientation and magnitude to characterize the input texture variations. We then introduce a guided texture synthesis algorithm to synthesize a texture resembling the reference texture with the input texture variations. The main contribution of our algorithm is its ability to locally deform the reference texture according to local texture descriptors in order to better reproduce the input texture variations. We show that our approach is able to produce results comparable with current state-of-the-art approaches but with fewer user inputs.
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Submitted on : Thursday, May 11, 2017 - 11:16:53 AM
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Benoit Arbelot, Romain Vergne, Thomas Hurtut, Joëlle Thollot. Texture Transfer Based on Texture Descriptor Variations. [Research Report] RR-9067, Inria. 2017. ⟨hal-01520226⟩

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