Parallel Controllable Texture Synthesis Sylvain Lefebvre, Hugues Hoppe SIGGRAPH 2005 24(3), 777-786.

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Presentation transcript:

Parallel Controllable Texture Synthesis Sylvain Lefebvre, Hugues Hoppe SIGGRAPH (3),

Parallel Controllable Texture Synthesis 2 Outline Introduction Parallel synthesis method Synthesis control Result

Parallel Controllable Texture Synthesis 3 Introduction Sample-based texture synthesis analyzes a given exemplar to create visually similar images. – tiling methods are the fastest – patch optimization methods produce some of the best results – neighborhood-matching algorithms allow greater fine-scale adaptability Our interest is in applying synthesis to define infinite, aperiodic, deterministic content from a compact representation. we present a new neighborhood- matching method.

Parallel Controllable Texture Synthesis 4 Parallel synthesis method – Basic scheme E[u]=E[S[p]] –E: m×m exemplar image –S: synthesized image –p ∈ Z 2 –u ∈ Z 2 image pyramid S 0, S 1, …, (S L =S) in coarse-to-fine order, where L=log 2 m. (Figure 2)

Parallel Controllable Texture Synthesis 5 Parallel synthesis method – steps

Parallel Controllable Texture Synthesis 6 Parallel synthesis method – Upsampling & Jitter –h l regular output spacing : 1 for pyramid, 2 L-1 for a stack –Hash Function H: Z 2 -> [-1,+1] 2 –per-level randomness parameter r l : [0,1]

Parallel Controllable Texture Synthesis 7 Parallel synthesis method – Correction For each pixel p, we gather the pixel colors of its 5×5 neighbor-hood at the current level, represented as a vector N Sl (p). This neighborhood is compared with exemplar neighborhoods N El (u) to find the L 2 best matching one.

Parallel Controllable Texture Synthesis 8 Parallel synthesis method – Gaussian image stack traditional Gaussian image pyramid often results in synthesized features that align with a coarser “grid”. because ancestor coordinates in the synthesis pyramid are snapped to the quantized positions of the exemplar pyramid.

Parallel Controllable Texture Synthesis 9 Parallel synthesis method – Gaussian image stack augment the exemplar image on all sides to have size 2m×2m: –an actual larger texture –a tiling if the exemplar is toroidal –reflected copies of the exemplar Gaussian filtering each level, without subsampling. Reassign h l = 2 L-l.

Synthesis control – Multiscale randomness control The randomness parameters r l set the jitter amplitude at each level, and thus provide a form of “spectral variation control”.

Parallel Controllable Texture Synthesis 11 Synthesis control – Spatial modulation over source preserving the integrity of selected texture elements in nonstationary textures.

Parallel Controllable Texture Synthesis 12 Synthesis control – Spatial modulation over output to roughen a surface pattern in areas of wear or damage.

Synthesis control – Feature drag-and-drop S l [p]:=((u F )+(p-p F )) mod m if ||p-p F || < r F –p F : the desired exemplar coordinate –r F : exemplar radius –u F : circle center r F = r i l/L + r o (L-l)/L –r i : inner radius –r o : outer radius

Parallel Controllable Texture Synthesis 14 Result additional results