Model Synthesis: A General Procedural Modeling Algorithm.
ABSTRACT We present a method for procedurally modeling general complex 3D shapes. Our approach can automatically generate complex models of buildings, man-made structures, or urban datasets in a few minutes based on user-defined inputs. The algorithm attempts to generate complex 3D models that resemble a user-defined input model and that satisfy various dimensional, geometric, and algebraic constraints to control the shape. These constraints are used to capture the intent of the user and generate shapes that look more natural. We also describe efficient techniques to handle complex shapes, highlight its performance on many different types of models. We compare model synthesis algorithms with other procedural modeling techniques, discuss the advantages of different approaches, and describe as close connection between model synthesis and context-sensitive grammars.
- [Show abstract] [Hide abstract]
ABSTRACT: Solid textures, comprising 3D particles embedded in a matrix in a regular or semiregular pattern, are common in natural and man-made materials, such as brickwork, stone walls, plant cells in a leaf, etc. We present a novel technique for synthesizing such textures, starting from 2D image exemplars which provide cross-sections of the desired volume texture. The shapes and colors of typical particles embedded in the structure are estimated from their 2D cross-sections. Particle positions in the texture images are also used to guide spatial placement of the 3D particles during synthesis of the 3D texture. Our experiments demonstrate that our algorithm can produce higher quality structures than previous approaches; they are both compatible with the input images, and have a plausible 3D nature.IEEE Transactions on Visualization and Computer Graphics 01/2013; 19(3):460-469. · 1.90 Impact Factor
Article: Synthesis of 3D models by Petri net[Show abstract] [Hide abstract]
ABSTRACT: This paper presents a synthesis method for 3D models using Petri net. Feature structure units from the example model are extracted, along with their constraints, through structure analysis, to create a new model using an inference method based on Petri net. Our method has two main advantages: first, 3D model pieces are delineated as the feature structure units and Petri net is used to record their shape features and their constraints in order to outline the model, including extending and deforming operations; second, a construction space generating algorithm is presented to convert the curve drawn by the user into local shape controlling parameters, and the free form deformation (FFD) algorithm is used in the inference process to deform the feature structure units. Experimental results showed that the proposed method can create large-scale complex scenes or models and allow users to effectively control the model result.Journal of Zhejiang University: Science C 14(7). · 0.30 Impact Factor