Pyramid-based texture analysis/synthesis
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Solid texturing of complex surfaces
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Interactive Image-based Modeling of Macrostructured Textures
IEEE Computer Graphics and Applications
The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simulation of natural scenes using textured quadric surfaces
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Texture synthesis from multiple sources
ACM SIGGRAPH 2003 Sketches & Applications
Stereological techniques for solid textures
ACM SIGGRAPH 2004 Papers
Solid texture synthesis from 2D exemplars
ACM SIGGRAPH 2007 papers
Lapped solid textures: filling a model with anisotropic textures
ACM SIGGRAPH 2008 papers
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Numerous techniques have been proposed to successfully synthesize two-dimensional (2D) textures in terms of quality and performance. Three-dimensional (3D) or solid texture synthesis, on the other hand, remains relatively unexplored due to its higher complexity. There are several types of existing algorithms for solid texture synthesis, and among them, the outstanding work by Jagnow et al. opens a new door for solid texture synthesis of discrete particles; however, their work leaves two important issues unaddressed. First, without the help of stereology, users need to explicitly provide the 3D shapes of target particles for synthesis. Second, the locations and orientations of the 3D particles are resolved by a simulated annealing method, which is intrinsically a non-deterministic approach, and thus the optimality is not always guaranteed. To solve the shape problem, we propose a simple algorithm that applies the idea of visual hulls to approximate the shapes of 3D particles when only a 2D image is given; to solve the location and orientation problem, we design a deterministic algorithm that can place these desired 3D particles in space more properly. Additionally we also propose a method to further couple the color and size information of particles to achieve an even better resemblance to the 2D image.