Multi-scale Assemblage for Procedural Texturing

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1. What are the contributions mentioned in the paper "Multi-scale assemblage for procedural texturing" ?

2. What are the future works mentioned in the paper "Multi-scale assemblage for procedural texturing" ?

3. How can the authors define complex natural textures?

4. What is the condition for a periodic tessellation of the plane?

Accepted Answer

This paper presents two main contributions: 1 ) a new procedural random point distribution function, that, unlike point jittering, allow us to take into account some spatial dependencies among figures and 2 ) a “ multi-variate ” approach that, instead of defining finite sets of constant figures, allows us to generate nearly infinite variations of figures on-the-fly.. For both, the authors use a “ statistical shape model ”, which is a representation of shape variations.

Accepted Answer

Another future work will consist in extending their 2D assemblage technique to the 3D case, so as to be able to edit procedural solid textures.

Accepted Answer

As for classical bombing, complex natural textures can be defined by using textured polygons instead of kernel functions (which are rather used to define resolution independent texture basis functions).

Accepted Answer

The only condition is that the set of cells forms a periodic rectilinear tessellation of the plane, i.e. there are no gaps and no overlaps between cells.

Accepted Answer

figures and subfigures can be associated to crops of texture photographs to produce high definition virtual textures for real-time rendering application.

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Random point distributions are fundamental for procedural texturing, since they represent a support function for several other procedural basis functions: sparse convolution noises [Lew89, vW91, LLDD09], cellular noises computed using n-th closest distances [Wor96] and bombing patterns consisting of randomly “dropped” figures, that are for example textured quads in [Gla04].

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The amplitude of deformation resulting from each Ψ j can be evaluated by making the vector of weights vary at the corresponding eigenvalue λ j, while setting all other weights to 0: w = (0, · · · ,0,a j,0, · · · ,0).

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Their most interesting advantage is the ability to generate visual complexity with quasi-infinite variation at arbitrary definition while requiring only a marginal memory cost.

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By drawing the set of figure samples used for statistical learning, for both the cells and the kernels, the user directly and interactively models a corresponding procedural texture.

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Φ represents a geometric primitive that is used to define object positions, similarly to the way the authors used figures to define transformations

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Another limitation is that the authors pre-defined a finite set of interpolation / distance functions for creating resolution independent texture basis functions.

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while increasing texture complexity improves visual quality, it also raises more and more problems concerning: 1) excessive storage requirements and 2) prohibitive synthe-sis timings.

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Their assemblage method can also be used as a high-definition interactive texturing technique (40/100 fps with/without displacement mapping), as shown by the close-ups of the tree in figure 13.

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Another future work will consist in extending their 2D assemblage technique to the 3D case, so as to be able to edit procedural solid textures.

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The leaves-covered floor shown in figure 11 shows the variety of appearances and phenomena, such as ageing, that can be represented using their technique.

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The GPU implementation the authors presented allows us to texture at real-time rates very large, potentially infinite surfaces at low memory cost without repetition.

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In this specific context, procedural means that texture values are explicitly computed by functions at run-time instead of fetching them from data arrays (texture maps).

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using [PTMG08], each leaf can be rendered at real-time (70 fps) with a unique appearance by using a stochastic combination of two subfigures (with a stochastic palettized coloration)stored in GPU texture memory.

Accepted Answer

The classes of patterns that can be represented is limited by the narrow range of available procedural basis functions, the most common ones being noise and turbulence (a sum of noises) [Per85].

Multi-scale Assemblage for Procedural Texturing

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Most frequently asked questions

1. What are the contributions mentioned in the paper "Multi-scale assemblage for procedural texturing" ?

2. What are the future works mentioned in the paper "Multi-scale assemblage for procedural texturing" ?

3. How can the authors define complex natural textures?

4. What is the condition for a periodic tessellation of the plane?

5. How can a texture be used to represent a mosaic-stone pattern?

6. What are the main categories of basis functions for procedural texturing?

7. How can the authors evaluate the amplitude of deformation resulting from each j?

8. What is the interesting advantage of procedural textures?

9. How can the authors model a procedural texture?

10. What is the definition of a geometric primitive?

11. What is the limitation of the assemblage method?

12. What are the main problems of increasing texture complexity?

13. What is the use of their method for generating 3D textures?

14. What is the next step in the assemblage technique?

15. What is the texture used to represent the leaves covered floor?

16. How can the authors use the GPU to texture at real-time rates?

17. What is the definition of procedural texture?

18. How can the authors render a leaf at real-time?

19. What are the common procedural basis functions?

Figures

Citations

Generating vast varieties of realistic leaves with parametric 2Gmap L-systems

Procedural texture synthesis by locally controlled spot noise

A Survey of Control Mechanisms for Creative Pattern Generation

Local spot noise for procedural surface details synthesis

Modélisation par bruit procédural et rendu de détails volumiques de surfaces dans les scènes virtuelles

References

The Fractal Geometry of Nature

Statistical Shape Analysis: With Applications in R

SCAPE: shape completion and animation of people

An image synthesizer

GPU Computing

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