【SIGGRAPH Asia 2012专题*技术论文】获取性和综合型室内场景：基于实例的合成三维物体案例

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【SIGGRAPH Asia 2012专题*技术论文】

获取性和综合型室内场景：基于实例的合成三维物体案例

Example-based Synthesis of 3D Object Arrangements

Matthew Fisher, Daniel Ritchie, Manolis Savva, Thomas Funkhouser, Pat Hanrahan




摘要：我们提出一个方法合成三维对象安排的例子。给一些用户提供的例子，我们的系统可以合成不同的一套可行的新场景的学习从一个较大的场景数据库。我们依靠的三个新贡献。首先，我们引入概率模型场景的基于贝叶斯网络和高斯混合物，可以训练，从一个小数目，输入的例子。其次，我们制定一个聚类算法，群体对象数据库中发生的场景，根据他们的地方社区。这些类允许在合成过程中对各种类型的对象为互换。第三，我们训练我们的概率模型上的混合用户提供的实例和相关的场景从数据库中检索。这种混合模型的学习过程是可以控制引入更多品种的合成场景。我们评价我们的算法，通过定性结果和知觉的研究中，参与者判断合成场景是非常合理的，相比hand-created场景。
Abstract：We present a method for synthesizing 3D object arrangements from examples. Given a few user-provided examples, our system can synthesize a diverse set of plausible new scenes by learning from a larger scene database. We rely on three novel contributions. First,we introduce a probabilistic model for scenes based on Bayesian networks and Gaussian mixtures that can be trained from a small number of input examples. Second, we develop a clustering algorithm that groups objects occurring in a database of scenes according to their local scene neighborhoods. These contextual categories allow the synthesis process to treat a wider variety of objects as interchangeable. Third, we train our probabilistic model on a mix of user-provided examples and relevant scenes retrieved from the database. This mixed model learning process can be controlled to introduce additional variety into the synthesized scenes. We evaluate our algorithm through qualitative results and a perceptual study in which participants judged synthesized scenes to be highly plausible, as compared to hand-created scenes.
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