Model Synthesis: A General Procedural Modeling Algorithm

University of North Carolina at Chapel Hill, Chapel Hill.
IEEE transactions on visualization and computer graphics 08/2010; 17(6). DOI: 10.1109/TVCG.2010.112
Source: PubMed


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.

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    • "The existing methods for analysis of model structure are mainly divided into the following two types. The one type is structural analysis method based on manual splitting [9] [22] "
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    ABSTRACT: In this paper we present a convenient building model synthesis method. It aims at obtaining new user-defined building models through seamless stitching after synthesis of each single building facade. During the optimization process of synthesis of each single building facade, we utilize model structure analysis method to obtain the smallest structural units and the constraint graph among them, transforming complicated three-dimension (3D) synthesis problem into two-dimension (2D) constraint graph synthesis problem. Then we construct a global energy function and minimize it through iterative optimization with expectation maximization algorithm, in order to obtain new objective constraint graph. During stitching process, in order to get complete model synthesis result, we replace objective constraint graph with structural unit to transform synthesis back into 3D space, and achieve automatic stitching between neighboring construction units and neighboring facades by using the connection point sets of structural units in original samples. The experiment results demonstrate our method can generate building models of absolutely different styles quickly and efficiently based on single or multiple samples, while maintaining the continuity and visual integrity of result models well.
    Graphical Models 09/2014; 76(5). DOI:10.1016/j.gmod.2014.03.018 · 1.05 Impact Factor
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    • "Another related work is the model synthesis method presented by Merrell et al[13] [14] [15]. This method extends the size of the example model by recombining the model pieces. "
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    ABSTRACT: This paper presents an intent-driven model synthesis method. The method introduces an interactive straight prismatic construction space to realize the structure and shape variation of the example model simultaneously. The construction space defines the global size and the local shape feature of the desired model. Users can draw a closed curve and some skeleton lines by a sketch-based interface to design the construction space. Our algorithm first uses a quadrangulation algorithm to create a subdivision plane with the same contour as the closed curve. And the drawn skeleton lines control the local orientation of split units in the plane. Then it creates the construction space by sweeping the subdivision plane. Finally, it fills the construction space with the deformed model pieces while maintaining the generalized adjacent constraints, which are defined according to the example model. We demonstrate the effectiveness of the approach on large-scale complex models such as architecture, mountains.
    Proceedings of the 6th International Symposium on Visual Information Communication and Interaction; 08/2013
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    • "As shown in Fig. 11, the distribution in the normal histogram depicting the results obtained using our proposed method is different from that in the example histogram, while that obtained using Merrell and Manocha (2011)'s method is quite similar to that of the example one. The discriminations between the histograms can be measured by "
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    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 07/2013; 14(7). DOI:10.1631/jzus.CIDE1305 · 0.42 Impact Factor
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